From 8f5ec509936845e0545f0488b6678b11ed0c11d9 Mon Sep 17 00:00:00 2001
From: jcasals <jcasals@iri.upc.edu>
Date: Wed, 31 Jul 2019 10:06:14 +0200
Subject: [PATCH] Clean demos
---
demos/CMakeLists.txt | 228 -
demos/demo_2_lasers_offline.cpp | 321 -
demos/demo_ORB.png | Bin 10936 -> 0 bytes
demos/demo_analytic_odom_factor.cpp | 314 -
demos/demo_apriltag.cpp | 290 -
demos/demo_autodiff.cpp | 422 -
demos/demo_capture_laser_2D.cpp | 134 -
demos/demo_ceres_2_lasers.cpp | 420 -
demos/demo_ceres_2_lasers_polylines.cpp | 377 -
demos/demo_diff_drive.cpp | 297 -
demos/demo_eigen_quaternion.cpp | 34 -
demos/demo_eigen_template.cpp | 105 -
demos/demo_factor_AHP.cpp | 148 -
demos/demo_factor_imu.cpp | 279 -
demos/demo_factor_odom_3D.cpp | 13 -
demos/demo_faramotics_simulation.cpp | 244 -
demos/demo_fcn_ptr.cpp | 130 -
demos/demo_gazebo_x-10cm_y-20cm.jpg | Bin 204082 -> 0 bytes
demos/demo_gazebo_x-10cm_y00cm.jpg | Bin 207132 -> 0 bytes
demos/demo_gazebo_x-20cm_y-10cm.jpg | Bin 209428 -> 0 bytes
demos/demo_gazebo_x-20cm_y-20cm.jpg | Bin 207363 -> 0 bytes
demos/demo_gazebo_x-20cm_y00cm.jpg | Bin 209575 -> 0 bytes
demos/demo_gazebo_x00cm_y-10cm.jpg | Bin 207874 -> 0 bytes
demos/demo_gazebo_x00cm_y-20cm.jpg | Bin 206526 -> 0 bytes
demos/demo_gazebo_x00cm_y00cm.jpg | Bin 209086 -> 0 bytes
demos/demo_image.cpp | 177 -
demos/demo_imuDock.cpp | 318 -
demos/demo_imuDock_autoKFs.cpp | 311 -
demos/demo_imuPlateform_Offline.cpp | 266 -
demos/demo_imu_constrained0.cpp | 374 -
demos/demo_kf_callback.cpp | 72 -
demos/demo_list_remove.cpp | 61 -
demos/demo_map_yaml.cpp | 101 -
demos/demo_matrix_prod.cpp | 187 -
demos/demo_mpu.cpp | 233 -
demos/demo_polylines.cpp | 305 -
demos/demo_processor_imu.cpp | 214 -
demos/demo_processor_imu_jacobians.cpp | 418 -
demos/demo_processor_odom_3D.cpp | 100 -
demos/demo_processor_tracker_feature.cpp | 57 -
demos/demo_processor_tracker_landmark.cpp | 95 -
.../demo_processor_tracker_landmark_image.cpp | 254 -
demos/demo_projection_points.cpp | 468 -
demos/demo_sh_ptr.cpp | 795 --
demos/demo_simple_AHP.cpp | 257 -
demos/demo_sort_keyframes.cpp | 79 -
demos/demo_sparsification.cpp | 314 -
demos/demo_state_quaternion.cpp | 39 -
demos/demo_tracker_ORB.cpp | 267 -
demos/demo_virtual_hierarchy.cpp | 354 -
demos/demo_wolf_autodiffwrapper.cpp | 316 -
demos/demo_wolf_factories.cpp | 107 -
demos/demo_wolf_imported_graph.cpp | 415 -
demos/demo_wolf_logging.cpp | 24 -
demos/demo_wolf_prunning.cpp | 566 --
demos/demo_wolf_root.cpp | 19 -
demos/demo_wolf_tree.cpp | 59 -
demos/demo_yaml.cpp | 94 -
demos/demo_yaml_conversions.cpp | 54 -
demos/input_M3500b_toro.graph | 8953 -----------------
demos/maps/map_apriltag_logitech_1234.yaml | 46 -
demos/solver/test_SPQR.cpp | 92 -
demos/solver/test_ccolamd.cpp | 130 -
demos/solver/test_ccolamd_blocks.cpp | 180 -
demos/solver/test_iQR.cpp | 350 -
demos/solver/test_iQR_wolf.cpp | 560 --
demos/solver/test_iQR_wolf2.cpp | 430 -
.../test_incremental_ccolamd_blocks.cpp | 262 -
demos/solver/test_permutations.cpp | 113 -
69 files changed, 22642 deletions(-)
delete mode 100644 demos/CMakeLists.txt
delete mode 100644 demos/demo_2_lasers_offline.cpp
delete mode 100644 demos/demo_ORB.png
delete mode 100644 demos/demo_analytic_odom_factor.cpp
delete mode 100644 demos/demo_apriltag.cpp
delete mode 100644 demos/demo_autodiff.cpp
delete mode 100644 demos/demo_capture_laser_2D.cpp
delete mode 100644 demos/demo_ceres_2_lasers.cpp
delete mode 100644 demos/demo_ceres_2_lasers_polylines.cpp
delete mode 100644 demos/demo_diff_drive.cpp
delete mode 100644 demos/demo_eigen_quaternion.cpp
delete mode 100644 demos/demo_eigen_template.cpp
delete mode 100644 demos/demo_factor_AHP.cpp
delete mode 100644 demos/demo_factor_imu.cpp
delete mode 100644 demos/demo_factor_odom_3D.cpp
delete mode 100644 demos/demo_faramotics_simulation.cpp
delete mode 100644 demos/demo_fcn_ptr.cpp
delete mode 100644 demos/demo_gazebo_x-10cm_y-20cm.jpg
delete mode 100644 demos/demo_gazebo_x-10cm_y00cm.jpg
delete mode 100644 demos/demo_gazebo_x-20cm_y-10cm.jpg
delete mode 100644 demos/demo_gazebo_x-20cm_y-20cm.jpg
delete mode 100644 demos/demo_gazebo_x-20cm_y00cm.jpg
delete mode 100644 demos/demo_gazebo_x00cm_y-10cm.jpg
delete mode 100644 demos/demo_gazebo_x00cm_y-20cm.jpg
delete mode 100644 demos/demo_gazebo_x00cm_y00cm.jpg
delete mode 100644 demos/demo_image.cpp
delete mode 100644 demos/demo_imuDock.cpp
delete mode 100644 demos/demo_imuDock_autoKFs.cpp
delete mode 100644 demos/demo_imuPlateform_Offline.cpp
delete mode 100644 demos/demo_imu_constrained0.cpp
delete mode 100644 demos/demo_kf_callback.cpp
delete mode 100644 demos/demo_list_remove.cpp
delete mode 100644 demos/demo_map_yaml.cpp
delete mode 100644 demos/demo_matrix_prod.cpp
delete mode 100644 demos/demo_mpu.cpp
delete mode 100644 demos/demo_polylines.cpp
delete mode 100644 demos/demo_processor_imu.cpp
delete mode 100644 demos/demo_processor_imu_jacobians.cpp
delete mode 100644 demos/demo_processor_odom_3D.cpp
delete mode 100644 demos/demo_processor_tracker_feature.cpp
delete mode 100644 demos/demo_processor_tracker_landmark.cpp
delete mode 100644 demos/demo_processor_tracker_landmark_image.cpp
delete mode 100644 demos/demo_projection_points.cpp
delete mode 100644 demos/demo_sh_ptr.cpp
delete mode 100644 demos/demo_simple_AHP.cpp
delete mode 100644 demos/demo_sort_keyframes.cpp
delete mode 100644 demos/demo_sparsification.cpp
delete mode 100644 demos/demo_state_quaternion.cpp
delete mode 100644 demos/demo_tracker_ORB.cpp
delete mode 100644 demos/demo_virtual_hierarchy.cpp
delete mode 100644 demos/demo_wolf_autodiffwrapper.cpp
delete mode 100644 demos/demo_wolf_factories.cpp
delete mode 100644 demos/demo_wolf_imported_graph.cpp
delete mode 100644 demos/demo_wolf_logging.cpp
delete mode 100644 demos/demo_wolf_prunning.cpp
delete mode 100644 demos/demo_wolf_root.cpp
delete mode 100644 demos/demo_wolf_tree.cpp
delete mode 100644 demos/demo_yaml.cpp
delete mode 100644 demos/demo_yaml_conversions.cpp
delete mode 100644 demos/input_M3500b_toro.graph
delete mode 100644 demos/maps/map_apriltag_logitech_1234.yaml
delete mode 100644 demos/solver/test_SPQR.cpp
delete mode 100644 demos/solver/test_ccolamd.cpp
delete mode 100644 demos/solver/test_ccolamd_blocks.cpp
delete mode 100644 demos/solver/test_iQR.cpp
delete mode 100644 demos/solver/test_iQR_wolf.cpp
delete mode 100644 demos/solver/test_iQR_wolf2.cpp
delete mode 100644 demos/solver/test_incremental_ccolamd_blocks.cpp
delete mode 100644 demos/solver/test_permutations.cpp
diff --git a/demos/CMakeLists.txt b/demos/CMakeLists.txt
deleted file mode 100644
index 6ee86ed12..000000000
--- a/demos/CMakeLists.txt
+++ /dev/null
@@ -1,228 +0,0 @@
-# Dynamically remove objects from list
-# add_executable(test_list_remove test_list_remove.cpp)
-
-# Matrix product test
-#ADD_EXECUTABLE(test_matrix_prod test_matrix_prod.cpp)
-
-#ADD_EXECUTABLE(test_eigen_template test_eigen_template.cpp)
-
-ADD_EXECUTABLE(test_fcn_ptr test_fcn_ptr.cpp)
-
-ADD_EXECUTABLE(test_kf_callback test_kf_callback.cpp)
-TARGET_LINK_LIBRARIES(test_kf_callback ${PROJECT_NAME})
-
-ADD_EXECUTABLE(test_wolf_logging test_wolf_logging.cpp)
-TARGET_LINK_LIBRARIES(test_wolf_logging ${PROJECT_NAME})
-
-IF(Ceres_FOUND)
- # test_processor_odom_3D
- ADD_EXECUTABLE(test_processor_odom_3D test_processor_odom_3D.cpp)
- TARGET_LINK_LIBRARIES(test_processor_odom_3D ${PROJECT_NAME})
-
-# ADD_EXECUTABLE(test_motion_2d test_motion_2d.cpp)
-# TARGET_LINK_LIBRARIES(test_motion_2d ${PROJECT_NAME})
-ENDIF(Ceres_FOUND)
-
-
-
-
-# State blocks with local parametrizations test
-#ADD_EXECUTABLE(test_state_quaternion test_state_quaternion.cpp)
-#TARGET_LINK_LIBRARIES(test_state_quaternion ${PROJECT_NAME})
-
-# Testing Eigen Permutations
-#ADD_EXECUTABLE(test_permutations solver/test_permutations.cpp)
-#TARGET_LINK_LIBRARIES(test_permutations ${PROJECT_NAME})
-
-# Enable Yaml config files
-IF(YAMLCPP_FOUND)
-# ADD_EXECUTABLE(test_yaml test_yaml.cpp)
-# TARGET_LINK_LIBRARIES(test_yaml ${PROJECT_NAME})
-
-# ADD_EXECUTABLE(test_yaml_conversions test_yaml_conversions.cpp)
-# TARGET_LINK_LIBRARIES(test_yaml_conversions ${PROJECT_NAME})
-
- # SensorFactory classes test
-# ADD_EXECUTABLE(test_wolf_factories test_wolf_factories.cpp)
-# TARGET_LINK_LIBRARIES(test_wolf_factories ${PROJECT_NAME})
-
- # Map load and save test
-# ADD_EXECUTABLE(test_map_yaml test_map_yaml.cpp)
-# TARGET_LINK_LIBRARIES(test_map_yaml ${PROJECT_NAME})
-ENDIF(YAMLCPP_FOUND)
-
-IF(Suitesparse_FOUND)
-IF (0) # These cannot compile on MacOSX -- we'll fix it some day.
- # Testing a ccolamd test
- ADD_EXECUTABLE(test_ccolamd solver/test_ccolamd.cpp)
- TARGET_LINK_LIBRARIES(test_ccolamd ${PROJECT_NAME})
-
- # Testing a blocks ccolamd test
- ADD_EXECUTABLE(test_ccolamd_blocks solver/test_ccolamd_blocks.cpp)
- TARGET_LINK_LIBRARIES(test_ccolamd_blocks ${PROJECT_NAME})
-
- # Testing an incremental blocks ccolamd test
- ADD_EXECUTABLE(test_incremental_ccolamd_blocks solver/test_incremental_ccolamd_blocks.cpp)
- TARGET_LINK_LIBRARIES(test_incremental_ccolamd_blocks ${PROJECT_NAME})
-
- # Testing an incremental QR with block ccolamd test
- ADD_EXECUTABLE(test_iQR solver/test_iQR.cpp)
- TARGET_LINK_LIBRARIES(test_iQR ${PROJECT_NAME})
-
- # Testing QR solver test tending to wolf
- ADD_EXECUTABLE(test_iQR_wolf solver/test_iQR_wolf.cpp)
- TARGET_LINK_LIBRARIES(test_iQR_wolf ${PROJECT_NAME})
-
- # Testing SPQR simple test
- #ADD_EXECUTABLE(test_SPQR solver/test_SPQR.cpp)
- #TARGET_LINK_LIBRARIES(test_SPQR ${PROJECT_NAME})
-ENDIF(0)
-
-ENDIF(Suitesparse_FOUND)
-
-# Building and populating the wolf tree
-# ADD_EXECUTABLE(test_wolf_tree test_wolf_tree.cpp)
-# TARGET_LINK_LIBRARIES(test_wolf_tree ${PROJECT_NAME})
-
-# Building and populating the wolf tree from .graph file (TORO)
-#ADD_EXECUTABLE(test_wolf_imported_graph test_wolf_imported_graph.cpp)
-#TARGET_LINK_LIBRARIES(test_wolf_imported_graph ${PROJECT_NAME})
-
-# Comparing performance of wolf auto_diff and ceres auto_diff
-#ADD_EXECUTABLE(test_wolf_autodiffwrapper test_wolf_autodiffwrapper.cpp)
-#TARGET_LINK_LIBRARIES(test_wolf_autodiffwrapper ${PROJECT_NAME})
-
-# Prunning wolf tree from .graph file (TORO)
-#ADD_EXECUTABLE(test_wolf_prunning test_wolf_prunning.cpp)
-#TARGET_LINK_LIBRARIES(test_wolf_prunning ${PROJECT_NAME})
-
-# Sparsification from wolf tree from .graph file (TORO)
-ADD_EXECUTABLE(test_sparsification test_sparsification.cpp)
-TARGET_LINK_LIBRARIES(test_sparsification ${PROJECT_NAME})
-
-# Comparing analytic and autodiff odometry factors
-#ADD_EXECUTABLE(test_analytic_odom_factor test_analytic_odom_factor.cpp)
-#TARGET_LINK_LIBRARIES(test_analytic_odom_factor ${PROJECT_NAME})
-
-# Vision
-IF(vision_utils_FOUND)
-
- IF(Ceres_FOUND)
- # Testing many things for the 3D image odometry
- ADD_EXECUTABLE(test_image test_image.cpp)
- TARGET_LINK_LIBRARIES(test_image ${PROJECT_NAME})
-
- # Processor Image Landmark test
- ADD_EXECUTABLE(test_processor_tracker_landmark_image test_processor_tracker_landmark_image.cpp)
- TARGET_LINK_LIBRARIES(test_processor_tracker_landmark_image ${PROJECT_NAME})
-
- # Simple AHP test
- ADD_EXECUTABLE(test_simple_AHP test_simple_AHP.cpp)
- TARGET_LINK_LIBRARIES(test_simple_AHP ${PROJECT_NAME})
-
- IF (APRILTAG_LIBRARY)
- ADD_EXECUTABLE(test_apriltag test_apriltag.cpp)
- TARGET_LINK_LIBRARIES(test_apriltag ${PROJECT_NAME})
- ENDIF(APRILTAG_LIBRARY)
-
- ENDIF(Ceres_FOUND)
-
- # Testing OpenCV functions for projection of points
- ADD_EXECUTABLE(test_projection_points test_projection_points.cpp)
- TARGET_LINK_LIBRARIES(test_projection_points ${PROJECT_NAME})
-
- # Factor test
- ADD_EXECUTABLE(test_factor_AHP test_factor_AHP.cpp)
- TARGET_LINK_LIBRARIES(test_factor_AHP ${PROJECT_NAME})
-
- # ORB tracker test
- ADD_EXECUTABLE(test_tracker_ORB test_tracker_ORB.cpp)
- TARGET_LINK_LIBRARIES(test_tracker_ORB ${PROJECT_NAME})
-
-ENDIF(vision_utils_FOUND)
-
-# Processor Tracker Feature test
-ADD_EXECUTABLE(test_processor_tracker_feature test_processor_tracker_feature.cpp)
-TARGET_LINK_LIBRARIES(test_processor_tracker_feature ${PROJECT_NAME})
-
-# Processor Tracker Landmark test
-ADD_EXECUTABLE(test_processor_tracker_landmark test_processor_tracker_landmark.cpp)
-TARGET_LINK_LIBRARIES(test_processor_tracker_landmark ${PROJECT_NAME})
-
-# Processor IMU test
-ADD_EXECUTABLE(test_processor_imu test_processor_imu.cpp)
-TARGET_LINK_LIBRARIES(test_processor_imu ${PROJECT_NAME})
-
-# Processor Diff-Drive test
-ADD_EXECUTABLE(test_processor_diff_drive test_diff_drive.cpp)
-TARGET_LINK_LIBRARIES(test_processor_diff_drive ${PROJECT_NAME})
-
-# MPU6050 IMU test
-#ADD_EXECUTABLE(test_mpu test_mpu.cpp)
-#TARGET_LINK_LIBRARIES(test_mpu ${PROJECT_NAME})
-
-# Processor IMU - Jacobian checking test
-#ADD_EXECUTABLE(test_processor_imu_jacobians test_processor_imu_jacobians.cpp)
-#TARGET_LINK_LIBRARIES(test_processor_imu_jacobians ${PROJECT_NAME})
-
-# Test IMU using printed Dock
-#ADD_EXECUTABLE(test_imuDock test_imuDock.cpp)
-#TARGET_LINK_LIBRARIES(test_imuDock ${PROJECT_NAME})
-
-# Test IMU with auto KF generation (Humanoids 20017)
-#ADD_EXECUTABLE(test_imuDock_autoKFs test_imuDock_autoKFs.cpp)
-#TARGET_LINK_LIBRARIES(test_imuDock_autoKFs ${PROJECT_NAME})
-
-# FactorIMU - factors test
-#ADD_EXECUTABLE(test_imu_constrained0 test_imu_constrained0.cpp)
-#TARGET_LINK_LIBRARIES(test_imu_constrained0 ${PROJECT_NAME})
-
-# IMU - Offline plateform test
-#ADD_EXECUTABLE(test_imuPlateform_Offline test_imuPlateform_Offline.cpp)
-#TARGET_LINK_LIBRARIES(test_imuPlateform_Offline ${PROJECT_NAME})
-
-# IMU - factorIMU
-#ADD_EXECUTABLE(test_factor_imu test_factor_imu.cpp)
-#TARGET_LINK_LIBRARIES(test_factor_imu ${PROJECT_NAME})
-
-# IF (laser_scan_utils_FOUND)
-# ADD_EXECUTABLE(test_capture_laser_2D test_capture_laser_2D.cpp)
-# TARGET_LINK_LIBRARIES(test_capture_laser_2D ${PROJECT_NAME})
-# #ENDIF (laser_scan_utils_FOUND)
-
-# IF(faramotics_FOUND)
-# IF (laser_scan_utils_FOUND)
-# ADD_EXECUTABLE(test_ceres_2_lasers test_ceres_2_lasers.cpp)
-# TARGET_LINK_LIBRARIES(test_ceres_2_lasers
-# ${pose_state_time_LIBRARIES}
-# ${faramotics_LIBRARIES}
-# ${PROJECT_NAME})
-# ADD_EXECUTABLE(test_ceres_2_lasers_polylines test_ceres_2_lasers_polylines.cpp)
-# TARGET_LINK_LIBRARIES(test_ceres_2_lasers_polylines
-# ${pose_state_time_LIBRARIES}
-# ${faramotics_LIBRARIES}
-# ${PROJECT_NAME})
-# ADD_EXECUTABLE(test_2_lasers_offline test_2_lasers_offline.cpp)
-# TARGET_LINK_LIBRARIES(test_2_lasers_offline
-# ${pose_state_time_LIBRARIES}
-# ${faramotics_LIBRARIES}
-# ${PROJECT_NAME})
-# ADD_EXECUTABLE(test_faramotics_simulation test_faramotics_simulation.cpp)
-# TARGET_LINK_LIBRARIES(test_faramotics_simulation
-# ${pose_state_time_LIBRARIES}
-# ${faramotics_LIBRARIES}
-# ${PROJECT_NAME})
-# # ADD_EXECUTABLE(test_autodiff test_autodiff.cpp)
-# # TARGET_LINK_LIBRARIES(test_autodiff
-# # ${pose_state_time_LIBRARIES}
-# # ${faramotics_LIBRARIES}
-# # ${PROJECT_NAME})
-# # IF(Suitesparse_FOUND)
-# # ADD_EXECUTABLE(test_iQR_wolf2 solver/test_iQR_wolf2.cpp)
-# # TARGET_LINK_LIBRARIES(test_iQR_wolf2
-# # ${pose_state_time_LIBRARIES}
-# # ${faramotics_LIBRARIES}
-# # ${PROJECT_NAME})
-# # ENDIF(Suitesparse_FOUND)
-# # ENDIF (laser_scan_utils_FOUND)
-# # ENDIF(faramotics_FOUND)
diff --git a/demos/demo_2_lasers_offline.cpp b/demos/demo_2_lasers_offline.cpp
deleted file mode 100644
index 9174dc94f..000000000
--- a/demos/demo_2_lasers_offline.cpp
+++ /dev/null
@@ -1,321 +0,0 @@
-//std includes
-#include "base/sensor/sensor_GPS_fix.h"
-#include <cstdlib>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// Eigen includes
-#include <eigen3/Eigen/Dense>
-#include <eigen3/Eigen/Geometry>
-
-//Ceres includes
-#include "glog/logging.h"
-
-//Wolf includes
-#include "base/problem/problem.h"
-#include "base/processor/processor_tracker_landmark_corner.h"
-#include "base/processor/processor_odom_2D.h"
-#include "base/sensor/sensor_laser_2D.h"
-#include "base/sensor/sensor_odom_2D.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-
-// laserscanutils
-#include "laser_scan_utils/line_finder_iterative.h"
-#include "laser_scan_utils/laser_scan.h"
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-#include "base/capture/capture_pose.h"
-//faramotics includes
-#include "faramotics/dynamicSceneRender.h"
-#include "faramotics/rangeScan2D.h"
-#include "btr-headers/pose3d.h"
-
-void extractVector(std::ifstream& text_file, Eigen::VectorXs& vector, wolf::Scalar& ts)
-{
- std::string line;
- std::getline(text_file, line);
- std::stringstream line_stream(line);
- line_stream >> ts;
- for (auto i = 0; i < vector.size(); i++)
- line_stream >> vector(i);
-}
-
-void extractScan(std::ifstream& text_file, std::vector<float>& scan, wolf::Scalar& ts)
-{
- std::string line;
- std::getline(text_file, line);
- std::stringstream line_stream(line);
- line_stream >> ts;
- for (unsigned int i = 0; i < scan.size(); i++)
- line_stream >> scan[i];
-}
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- std::cout << "\n==================================================================\n";
- std::cout << "========== 2D Robot with offline odometry and 2 LIDARs =============\n";
-
- // USER INPUT ============================================================================================
- if (argc != 2 || atoi(argv[1]) < 1 )
- {
- std::cout << "Please call me with: [./test_ceres_manager NI PRINT], where:" << std::endl;
- std::cout << " - NI is the number of iterations (NI > 0)" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
-
- // FILES INPUT ============================================================================================
- std::ifstream laser_1_file, laser_2_file, odom_file, groundtruth_file;
- laser_1_file.open("simulated_laser_1.txt", std::ifstream::in);
- laser_2_file.open("simulated_laser_2.txt", std::ifstream::in);
- odom_file.open("simulated_odom.txt", std::ifstream::in);
- groundtruth_file.open("simulated_groundtruth.txt", std::ifstream::in);
-
- if (!(laser_1_file.is_open() && laser_2_file.is_open() && odom_file.is_open() && groundtruth_file.is_open()))
- {
- std::cout << "Error opening simulated data files. Remember to run test_faramotics_simulation before this test!" << std::endl;
- return -1;
- }
- else
- std::cout << "Simulated data files opened correctly..." << std::endl;
-
- unsigned int n_execution = (unsigned int) atoi(argv[1]); //number of iterations of the whole execution
-
- // INITIALIZATION ============================================================================================
- //init random generators
- Scalar odom_std_factor = 0.5;
- std::default_random_engine generator(1);
- std::normal_distribution<Scalar> distribution_odom(0.0, odom_std_factor); //odometry noise
-
- //variables
- std::string line;
- Eigen::VectorXs odom_data = Eigen::VectorXs::Zero(2);
- Eigen::VectorXs ground_truth(n_execution * 3); //all true poses
- Eigen::VectorXs ground_truth_pose(3); //last true pose
- Eigen::VectorXs odom_trajectory(n_execution * 3); //open loop trajectory
- Eigen::VectorXs mean_times = Eigen::VectorXs::Zero(6);
- clock_t t1, t2;
- Scalar timestamp;
- TimeStamp ts(0);
-
- // Wolf initialization
- Eigen::VectorXs odom_pose = Eigen::VectorXs::Zero(3);
- //Eigen::VectorXs gps_position = Eigen::VectorXs::Zero(2);
- Eigen::VectorXs laser_1_params(9), laser_2_params(9);
- Eigen::VectorXs laser_1_pose(4), laser_2_pose(4); //xyz + theta
- Eigen::VectorXs laser_1_pose2D(3), laser_2_pose2D(3); //xy + theta
-
- // odometry intrinsics
- IntrinsicsOdom2D odom_intrinsics;
- odom_intrinsics.k_disp_to_disp = odom_std_factor;
- odom_intrinsics.k_rot_to_rot = odom_std_factor;
-
- // laser 1 extrinsics and intrinsics
- extractVector(laser_1_file, laser_1_params, timestamp);
- extractVector(laser_1_file, laser_1_pose, timestamp);
- laser_1_pose2D.head<2>() = laser_1_pose.head<2>();
- laser_1_pose2D(2) = laser_1_pose(3);
- std::vector<float> scan1(laser_1_params(8)); // number of ranges in a scan
- IntrinsicsLaser2D laser_1_intrinsics;
- laser_1_intrinsics.scan_params = laserscanutils::LaserScanParams({laser_1_params(0), laser_1_params(1), laser_1_params(2), laser_1_params(3), laser_1_params(4), laser_1_params(5), laser_1_params(6), laser_1_params(7)});
-
- ProcessorParamsLaser laser_1_processor_params;
- laser_1_processor_params.line_finder_params_ = laserscanutils::LineFinderIterativeParams({0.1, 5, 1, 2});
- laser_1_processor_params.new_corners_th = 10;
-
- // laser 2 extrinsics and intrinsics
- extractVector(laser_2_file, laser_2_params, timestamp);
- extractVector(laser_2_file, laser_2_pose, timestamp);
- laser_2_pose2D.head<2>() = laser_2_pose.head<2>();
- laser_2_pose2D(2) = laser_2_pose(3);
- std::vector<float> scan2(laser_2_params(8));
- IntrinsicsLaser2D laser_2_intrinsics;
- laser_2_intrinsics.scan_params = laserscanutils::LaserScanParams({laser_2_params(0), laser_2_params(1), laser_2_params(2), laser_2_params(3), laser_2_params(4), laser_2_params(5), laser_2_params(6), laser_2_params(7)});
-
- ProcessorParamsLaser laser_2_processor_params;
- laser_2_processor_params.line_finder_params_ = laserscanutils::LineFinderIterativeParams({0.1, 5, 1, 2});
- laser_2_processor_params.new_corners_th = 10;
-
- Problem problem(FRM_PO_2D);
- SensorOdom2D* odom_sensor = (SensorOdom2D*)problem.installSensor("ODOM 2D", "odometer", odom_pose, &odom_intrinsics);
- ProcessorParamsOdom2D odom_params;
- odom_params.cov_det = 1;
- odom_params.dist_traveled_th_ = 5;
- odom_params.elapsed_time_th_ = 10;
- ProcessorOdom2D* odom_processor = (ProcessorOdom2D*)problem.installProcessor("ODOM 2D", "main odometry", odom_sensor, &odom_params);
- //SensorBasePtr gps_sensor = problem.installSensor("GPS FIX", "GPS fix", gps_position);
- SensorBasePtr laser_1_sensor = problem.installSensor("LASER 2D", "front laser", laser_1_pose2D, &laser_1_intrinsics);
- SensorBasePtr laser_2_sensor = problem.installSensor("LASER 2D", "rear laser", laser_2_pose2D, &laser_2_intrinsics);
- problem.installProcessor("LASER 2D", "front laser processor", laser_1_sensor, &laser_1_processor_params);
- problem.installProcessor("LASER 2D", "rear laser processor", laser_2_sensor, &laser_2_processor_params);
-
- std::cout << "Wolf tree setted correctly!" << std::endl;
-
- CaptureMotion* odom_capture = new CaptureMotion(ts, odom_sensor, odom_data, Eigen::Matrix2s::Identity() * odom_std_factor * odom_std_factor, nullptr);
-
- // Initial pose
- ground_truth_pose << 2, 8, 0;
- ground_truth.head(3) = ground_truth_pose;
- odom_trajectory.head(3) = ground_truth_pose;
-
- // Origin Key Frame with covariance
- problem.setPrior(ground_truth_pose, Eigen::Matrix3s::Identity() * 0.1, ts, 0.1);
-
- // Ceres wrapper
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- // ceres_options.minimizer_progress_to_stdout = false;
- // ceres_options.line_search_direction_type = ceres::LBFGS;
- // ceres_options.max_num_iterations = 100;
- google::InitGoogleLogging(argv[0]);
-
- CeresManager ceres_manager(&problem, ceres_options);
- std::ofstream log_file, landmark_file; //output file
-
- std::cout << "START TRAJECTORY..." << std::endl;
- // START TRAJECTORY ============================================================================================
- for (unsigned int step = 1; step < n_execution; step++)
- {
- //get init time
- t2 = clock();
-
- // GROUNDTRUTH ---------------------------
- //std::cout << "GROUND TRUTH..." << std::endl;
- t1 = clock();
- extractVector(groundtruth_file, ground_truth_pose, timestamp);
- ground_truth.segment(step * 3, 3) = ground_truth_pose;
-
- // timestamp
- ts = TimeStamp(timestamp);
-
- // ODOMETRY DATA -------------------------------------
- //std::cout << "ODOMETRY DATA..." << std::endl;
- extractVector(odom_file, odom_data, timestamp);
- // noisy odometry
- odom_data(0) += distribution_odom(generator) * (odom_data(0) == 0 ? 1e-6 : odom_data(0));
- odom_data(1) += distribution_odom(generator) * (odom_data(1) == 0 ? 1e-6 : odom_data(1));
- // process odometry
- odom_capture->setTimeStamp(TimeStamp(ts));
- odom_capture->setData(odom_data);
- odom_processor->process(odom_capture);
- // odometry integration
- odom_trajectory.segment(step * 3, 3) = problem.getCurrentState();
-
- // LIDAR DATA ---------------------------
- extractScan(laser_1_file, scan1, timestamp);
- extractScan(laser_2_file, scan2, timestamp);
- if (step % 3 == 0)
- {
- std::cout << "--PROCESS LIDAR 1 DATA..." << std::endl;
- CaptureLaser2D* new_scan_1 = new CaptureLaser2D(ts, laser_1_sensor, scan1);
- new_scan_1->process();
- std::cout << "--PROCESS LIDAR 2 DATA..." << std::endl;
- CaptureLaser2D* new_scan_2 = new CaptureLaser2D(ts, laser_2_sensor, scan2);
- new_scan_2->process();
- }
- mean_times(0) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // SOLVE OPTIMIZATION ---------------------------
- std::cout << "SOLVING..." << std::endl;
- t1 = clock();
- ceres::Solver::Summary summary = ceres_manager.solve();
- //std::cout << summary.FullReport() << std::endl;
- mean_times(3) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // COMPUTE COVARIANCES ---------------------------
- std::cout << "COMPUTING COVARIANCES..." << std::endl;
- t1 = clock();
- ceres_manager.computeCovariances();
- mean_times(4) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // TIME MANAGEMENT ---------------------------
- double total_t = ((double) clock() - t2) / CLOCKS_PER_SEC;
- mean_times(5) += total_t;
- if (total_t < 0.2)
- usleep(200000 - 1e6 * total_t);
-
-// std::cout << "\nTree after step..." << std::endl;
- }
-
- // DISPLAY RESULTS ============================================================================================
- mean_times /= n_execution;
- std::cout << "\nSIMULATION AVERAGE LOOP DURATION [s]" << std::endl;
- std::cout << " data reading: " << mean_times(0) << std::endl;
- std::cout << " wolf managing: " << mean_times(1) << std::endl;
- std::cout << " ceres managing: " << mean_times(2) << std::endl;
- std::cout << " ceres optimization: " << mean_times(3) << std::endl;
- std::cout << " ceres covariance: " << mean_times(4) << std::endl;
- std::cout << " loop time: " << mean_times(5) << std::endl;
-
- // std::cout << "\nTree before deleting..." << std::endl;
-
- // Print Final result in a file -------------------------
- // Vehicle poses
- int i = 0;
- Eigen::VectorXs state_poses = Eigen::VectorXs::Zero(n_execution * 3);
- for (auto frame : *(problem.getTrajectory()->getFrameList()))
- {
- state_poses.segment(i, 3) << frame->getP()->getVector(), frame->getO()->getVector();
- i += 3;
- }
-
- // Landmarks
- i = 0;
- Eigen::VectorXs landmarks = Eigen::VectorXs::Zero(problem.getMap()->getLandmarkList()->size() * 2);
- for (auto landmark : *(problem.getMap()->getLandmarkList()))
- {
- landmarks.segment(i, 2) = landmark->getP()->getVector();
- i += 2;
- }
-
- // Print log files
- std::string filepath = getenv("HOME") + std::string("/Desktop/log_file_2.txt");
- log_file.open(filepath, std::ofstream::out); //open log file
-
- if (log_file.is_open())
- {
- log_file << 0 << std::endl;
- for (unsigned int ii = 0; ii < n_execution; ii++)
- log_file << state_poses.segment(ii * 3, 3).transpose() << "\t" << ground_truth.segment(ii * 3, 3).transpose() << "\t" << (state_poses.segment(ii * 3, 3) - ground_truth.segment(ii * 3, 3)).transpose() << "\t" << odom_trajectory.segment(ii * 3, 3).transpose() << std::endl;
- log_file.close(); //close log file
- std::cout << std::endl << "Result file " << filepath << std::endl;
- }
- else
- std::cout << std::endl << "Failed to write the log file " << filepath << std::endl;
-
- std::string filepath2 = getenv("HOME") + std::string("/Desktop/landmarks_file_2.txt");
- landmark_file.open(filepath2, std::ofstream::out); //open log file
-
- if (landmark_file.is_open())
- {
- for (unsigned int ii = 0; ii < landmarks.size(); ii += 2)
- landmark_file << landmarks.segment(ii, 2).transpose() << std::endl;
- landmark_file.close(); //close log file
- std::cout << std::endl << "Landmark file " << filepath << std::endl;
- }
- else
- std::cout << std::endl << "Failed to write the landmark file " << filepath << std::endl;
-
- std::cout << "Press any key for ending... " << std::endl << std::endl;
- std::getchar();
-
- std::cout << "Problem:" << std::endl;
- std::cout << "Frames: " << problem.getTrajectory()->getFrameList().size() << std::endl;
- std::cout << "Landmarks: " << problem.getMap()->getLandmarkList()->size() << std::endl;
- std::cout << "Sensors: " << problem.getHardware()->getSensorList()->size() << std::endl;
-
- std::cout << " ========= END ===========" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_ORB.png b/demos/demo_ORB.png
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diff --git a/demos/demo_analytic_odom_factor.cpp b/demos/demo_analytic_odom_factor.cpp
deleted file mode 100644
index 32a2cbc64..000000000
--- a/demos/demo_analytic_odom_factor.cpp
+++ /dev/null
@@ -1,314 +0,0 @@
-// Testing creating wolf tree from imported .graph file
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-//std includes
-#include <iostream>
-#include <memory>
-#include <random>
-#include <cmath>
-#include <queue>
-
-//Wolf includes
-#include "wolf_manager.h"
-#include "core/capture/capture_void.h"
-#include "core/ceres_wrapper/ceres_manager.h"
-
-// EIGEN
-//#include <Eigen/CholmodSupport>
-
-namespace wolf {
-// inserts the sparse matrix 'ins' into the sparse matrix 'original' in the place given by 'row' and 'col' integers
-void insertSparseBlock(const Eigen::SparseMatrix<Scalar>& ins, Eigen::SparseMatrix<Scalar>& original, const unsigned int& row, const unsigned int& col)
-{
- for (int k=0; k<ins.outerSize(); ++k)
- for (Eigen::SparseMatrix<Scalar>::InnerIterator iti(ins,k); iti; ++iti)
- original.coeffRef(iti.row() + row, iti.col() + col) = iti.value();
-
- original.makeCompressed();
-}
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- //Welcome message
- std::cout << std::endl << " ========= WOLF IMPORTED .graph TEST ===========" << std::endl << std::endl;
-
- if (argc != 3 || atoi(argv[2]) < 0 )
- {
- std::cout << "Please call me with: [./test_wolf_imported_graph FILE_PATH MAX_VERTICES], where:" << std::endl;
- std::cout << " FILE_PATH is the .graph file path" << std::endl;
- std::cout << " MAX_VERTICES max edges to be loaded (0: ALL)" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
-
- // auxiliar variables
- std::string file_path_ = argv[1];
- unsigned int MAX_VERTEX = atoi(argv[2]);
- if (MAX_VERTEX == 0) MAX_VERTEX = 1e6;
- std::ifstream offLineFile_;
- ceres::Solver::Summary summary_autodiff, summary_analytic;
-
- // loading variables
- std::map<unsigned int, FrameBasePtr> index_2_frame_ptr_autodiff;
- std::map<unsigned int, FrameBasePtr> index_2_frame_ptr_analytic;
-
- // Wolf problem
- ProblemPtr wolf_problem_autodiff = new Problem(FRM_PO_2D);
- ProblemPtr wolf_problem_analytic = new Problem(FRM_PO_2D);
- SensorBasePtr sensor = new SensorBase("ODOM 2D", std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), std::make_shared<StateBlock>(Eigen::VectorXs::Zero(1)), std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), 2);
-
- // Ceres wrapper
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- ceres_options.max_num_iterations = 1e4;
- CeresManager* ceres_manager_autodiff = new CeresManager(wolf_problem_autodiff, ceres_options);
- CeresManager* ceres_manager_analytic = new CeresManager(wolf_problem_analytic, ceres_options);
-
- // load graph from .txt
- offLineFile_.open(file_path_.c_str(), std::ifstream::in);
- if (offLineFile_.is_open())
- {
- std::string buffer;
- unsigned int j = 0;
- // Line by line
- while (std::getline(offLineFile_, buffer))
- {
- //std::cout << "new line:" << buffer << std::endl;
- std::string bNum;
- unsigned int i = 0;
-
- // VERTEX
- if (buffer.at(0) == 'V')
- {
- //skip rest of VERTEX word
- while (buffer.at(i) != ' ') i++;
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //vertex index
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int vertex_index = atoi(bNum.c_str());
- bNum.clear();
-
- if (vertex_index <= MAX_VERTEX+1)
- {
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // vertex pose
- Eigen::Vector3s vertex_pose;
- // x
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // y
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // theta
- while (i < buffer.size() && buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(2) = atof(bNum.c_str());
- bNum.clear();
-
- // add frame to problem
- FrameBasePtr vertex_frame_ptr_autodiff = new FrameBase(TimeStamp(0), std::make_shared<StateBlock>(vertex_pose.head(2)), std::make_shared<StateBlock>(vertex_pose.tail(1)));
- FrameBasePtr vertex_frame_ptr_analytic = new FrameBase(TimeStamp(0), std::make_shared<StateBlock>(vertex_pose.head(2)), std::make_shared<StateBlock>(vertex_pose.tail(1)));
- wolf_problem_autodiff->getTrajectory()->addFrame(vertex_frame_ptr_autodiff);
- wolf_problem_analytic->getTrajectory()->addFrame(vertex_frame_ptr_analytic);
- // store
- index_2_frame_ptr_autodiff[vertex_index] = vertex_frame_ptr_autodiff;
- index_2_frame_ptr_analytic[vertex_index] = vertex_frame_ptr_analytic;
-
- //std::cout << "Added vertex! index: " << vertex_index << " id: " << vertex_frame_ptr_analytic->id() << std::endl << "pose: " << vertex_pose.transpose() << std::endl;
- }
- }
- // EDGE
- else if (buffer.at(0) == 'E')
- {
- j++;
- //skip rest of EDGE word
- while (buffer.at(i) != ' ') i++;
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //from
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int edge_old = atoi(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //to index
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int edge_new = atoi(bNum.c_str());
- bNum.clear();
-
- if (edge_new <= MAX_VERTEX+1 && edge_old <= MAX_VERTEX+1 )
- {
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // edge vector
- Eigen::Vector3s edge_vector;
- // x
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // y
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // theta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(2) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // edge covariance
- Eigen::Matrix3s edge_information;
- // xx
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // xy
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,1) = atof(bNum.c_str());
- edge_information(1,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // yy
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(1,1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // thetatheta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(2,2) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // xtheta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,2) = atof(bNum.c_str());
- edge_information(2,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // ytheta
- while (i < buffer.size() && buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(1,2) = atof(bNum.c_str());
- edge_information(2,1) = atof(bNum.c_str());
- bNum.clear();
-
- // add capture, feature and factor to problem
- FeatureBasePtr feature_ptr_autodiff = new FeatureBase("POSE", edge_vector, edge_information.inverse());
- CaptureVoid* capture_ptr_autodiff = new CaptureVoid(TimeStamp(0), sensor);
- assert(index_2_frame_ptr_autodiff.find(edge_old) != index_2_frame_ptr_autodiff.end() && "edge from vertex not added!");
- FrameBasePtr frame_old_ptr_autodiff = index_2_frame_ptr_autodiff[edge_old];
- assert(index_2_frame_ptr_autodiff.find(edge_new) != index_2_frame_ptr_autodiff.end() && "edge to vertex not added!");
- FrameBasePtr frame_new_ptr_autodiff = index_2_frame_ptr_autodiff[edge_new];
- frame_new_ptr_autodiff->addCapture(capture_ptr_autodiff);
- capture_ptr_autodiff->addFeature(feature_ptr_autodiff);
- FactorOdom2D* factor_ptr_autodiff = new FactorOdom2D(feature_ptr_autodiff, frame_old_ptr_autodiff);
- feature_ptr_autodiff->addFactor(factor_ptr_autodiff);
- //std::cout << "Added autodiff edge! " << factor_ptr_autodiff->id() << " from vertex " << factor_ptr_autodiff->getCapture()->getFrame()->id() << " to " << factor_ptr_autodiff->getFrameOther()->id() << std::endl;
-
- // add capture, feature and factor to problem
- FeatureBasePtr feature_ptr_analytic = new FeatureBase("POSE", edge_vector, edge_information.inverse());
- CaptureVoid* capture_ptr_analytic = new CaptureVoid(TimeStamp(0), sensor);
- assert(index_2_frame_ptr_analytic.find(edge_old) != index_2_frame_ptr_analytic.end() && "edge from vertex not added!");
- FrameBasePtr frame_old_ptr_analytic = index_2_frame_ptr_analytic[edge_old];
- assert(index_2_frame_ptr_analytic.find(edge_new) != index_2_frame_ptr_analytic.end() && "edge to vertex not added!");
- FrameBasePtr frame_new_ptr_analytic = index_2_frame_ptr_analytic[edge_new];
- frame_new_ptr_analytic->addCapture(capture_ptr_analytic);
- capture_ptr_analytic->addFeature(feature_ptr_analytic);
- FactorOdom2DAnalytic* factor_ptr_analytic = new FactorOdom2DAnalytic(feature_ptr_analytic, frame_old_ptr_analytic);
- feature_ptr_analytic->addFactor(factor_ptr_analytic);
- //std::cout << "Added analytic edge! " << factor_ptr_analytic->id() << " from vertex " << factor_ptr_analytic->getCapture()->getFrame()->id() << " to " << factor_ptr_analytic->getFrameOther()->id() << std::endl;
- //std::cout << "vector " << factor_ptr_analytic->getMeasurement().transpose() << std::endl;
- //std::cout << "information " << std::endl << edge_information << std::endl;
- //std::cout << "covariance " << std::endl << factor_ptr_analytic->getMeasurementCovariance() << std::endl;
- }
- }
- else
- assert("unknown line");
- }
- printf("\nGraph loaded!\n");
- }
- else
- printf("\nError opening file\n");
-
- // PRIOR
- FrameBasePtr first_frame_autodiff = wolf_problem_autodiff->getTrajectory()->getFrameList().front();
- FrameBasePtr first_frame_analytic = wolf_problem_analytic->getTrajectory()->getFrameList().front();
- CaptureFix* initial_covariance_autodiff = new CaptureFix(TimeStamp(0), new SensorBase("ABSOLUTE POSE", nullptr, nullptr, nullptr, 0), first_frame_autodiff->getState(), Eigen::Matrix3s::Identity() * 0.01);
- CaptureFix* initial_covariance_analytic = new CaptureFix(TimeStamp(0), new SensorBase("ABSOLUTE POSE", nullptr, nullptr, nullptr, 0), first_frame_analytic->getState(), Eigen::Matrix3s::Identity() * 0.01);
- first_frame_autodiff->addCapture(initial_covariance_autodiff);
- first_frame_analytic->addCapture(initial_covariance_analytic);
- initial_covariance_autodiff->emplaceFeatureAndFactor();
- initial_covariance_analytic->emplaceFeatureAndFactor();
-
- // SOLVING PROBLEMS
- std::cout << "solving..." << std::endl;
- std::cout << "ANALYTIC -----------------------------------" << std::endl;
- summary_analytic = ceres_manager_analytic->solve();
- std::cout << summary_analytic.FullReport() << std::endl;
- std::cout << "AUTODIFF -----------------------------------" << std::endl;
- summary_autodiff = ceres_manager_autodiff->solve();
- std::cout << summary_autodiff.FullReport() << std::endl;
-
- // COMPUTE COVARIANCES
- std::cout << "computing covariances..." << std::endl;
- std::cout << "ANALYTIC -----------------------------------" << std::endl;
- clock_t t1 = clock();
- ceres_manager_analytic->computeCovariances(ALL);//ALL_MARGINALS
- std::cout << "Time: " << ((double) clock() - t1) / CLOCKS_PER_SEC << "s" << std::endl;
- std::cout << "AUTODIFF -----------------------------------" << std::endl;
- t1 = clock();
- ceres_manager_autodiff->computeCovariances(ALL);//ALL_MARGINALS
- std::cout << "Time: " << ((double) clock() - t1) / CLOCKS_PER_SEC << "s" << std::endl;
-
- delete wolf_problem_autodiff; //not necessary to delete anything more, wolf will do it!
- std::cout << "wolf_problem_ deleted!" << std::endl;
- delete ceres_manager_autodiff;
- delete ceres_manager_analytic;
- std::cout << "ceres_manager deleted!" << std::endl;
- //End message
- std::cout << " =========================== END ===============================" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_apriltag.cpp b/demos/demo_apriltag.cpp
deleted file mode 100644
index 1230479ab..000000000
--- a/demos/demo_apriltag.cpp
+++ /dev/null
@@ -1,290 +0,0 @@
-/**
- * \file test_apriltag.cpp
- *
- * Created on: Dec 14, 2018
- * \author: Dinesh Atchtuhan
- */
-
-//Wolf
-#include "base/wolf.h"
-#include "base/rotations.h"
-#include "base/problem.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-#include "base/sensor/sensor_camera.h"
-#include "base/processor/processor_tracker_landmark_apriltag.h"
-#include "base/capture/capture_image.h"
-#include "base/feature/feature_apriltag.h"
-
-// opencv
-#include <opencv2/imgproc/imgproc.hpp>
-#include "opencv2/opencv.hpp"
-
-// Eigen
-#include <Eigen/Core>
-#include <Eigen/Geometry>
-
-// std
-#include <iostream>
-#include <stdlib.h>
-
-
-void draw_apriltag(cv::Mat image, std::vector<cv::Point2d> corners, int thickness=1, bool draw_corners=false);
-
-
-int main(int argc, char *argv[])
-{
- /*
- * HOW TO USE ?
- * For now, just call the executable and append the list of images to be processed.
- * The images must be placed in the root folder of your wolf project.
- * Ex:
- * ./test_apriltag frame1.jpg frame2.jpg frame3.jpg
- */
-
- using namespace wolf;
-
-
- // General execution options
- const bool APPLY_CONTRAST = false;
- const bool IMAGE_OUTPUT = true;
- const bool USEMAP = false;
-
-
- WOLF_INFO( "==================== processor apriltag test ======================" )
-
- std::string wolf_root = _WOLF_ROOT_DIR;
- // Wolf problem
- ProblemPtr problem = Problem::create("PO", 3);
- ceres::Solver::Options options;
- options.function_tolerance = 1e-6;
- options.max_num_iterations = 100;
- CeresManagerPtr ceres_manager = std::make_shared<CeresManager>(problem, options);
-
-
- WOLF_INFO( "==================== Configure Problem ======================" )
- Eigen::Vector7s cam_extrinsics; cam_extrinsics << 0,0,0, 0,0,0,1;
- SensorBasePtr sen = problem->installSensor("CAMERA", "camera", cam_extrinsics, wolf_root + "/src/examples/camera_logitech_c300_640_480.yaml");
-// SensorBasePtr sen = problem->installSensor("CAMERA", "camera", cam_extrinsics, wolf_root + "/src/examples/camera_Dinesh_LAAS_params_notangentrect.yaml");
- SensorCameraPtr sen_cam = std::static_pointer_cast<SensorCamera>(sen);
- ProcessorBasePtr prc = problem->installProcessor("TRACKER LANDMARK APRILTAG", "apriltags", "camera", wolf_root + "/src/examples/processor_tracker_landmark_apriltag.yaml");
-
- if (USEMAP){
- problem->loadMap(wolf_root + "/src/examples/maps/map_apriltag_logitech_1234.yaml");
- for (auto lmk : problem->getMap()->getLandmarkList()){
- lmk->fix();
- }
- }
-
- // set prior
- Eigen::Matrix6s covariance = Matrix6s::Identity();
- Scalar std_m;
- Scalar std_deg;
- if (USEMAP){
- std_m = 100; // standard deviation on original translation
- std_deg = 180; // standard deviation on original rotation
- }
- else {
- std_m = 0.00001; // standard deviation on original translation
- std_deg = 0.00001; // standard deviation on original rotation
- }
-
- covariance.topLeftCorner(3,3) = std_m*std_m * covariance.topLeftCorner(3,3);
- covariance.bottomRightCorner(3,3) = (M_TORAD*std_deg)*(M_TORAD*std_deg) * covariance.bottomRightCorner(3,3);
-
- if (USEMAP){
- FrameBasePtr F1 = problem->setPrior((Vector7s()<<0.08, 0.15, -0.75, 0, 0, 0, 1).finished(), covariance, 0.0, 0.1);
- }
- else {
- FrameBasePtr F1 = problem->setPrior((Vector7s()<<0,0,0,0,0,0,1).finished(), covariance, 0.0, 0.1);
- F1->fix();
- }
-
- // first argument is the name of the program.
- // following arguments are path to image (from wolf_root)
- const int inputs = argc -1;
- WOLF_DEBUG("nb of images: ", inputs);
- cv::Mat frame;
- Scalar ts(0);
- Scalar dt = 1;
-
- WOLF_INFO( "==================== Main loop ======================" )
- for (int input = 1; input <= inputs; input++) {
- std::string path = wolf_root + "/" + argv[input];
- frame = cv::imread(path, CV_LOAD_IMAGE_COLOR);
-
- if( frame.data ){ //if imread succeeded
-
- if (APPLY_CONTRAST){
- Scalar alpha = 2.0; // to tune contrast [1-3]
- int beta = 0; // to tune lightness [0-100]
- // Do the operation new_image(i,j) = alpha*image(i,j) + beta
- for( int y = 0; y < frame.rows; y++ ){
- for( int x = 0; x < frame.cols; x++ ){
- for( int c = 0; c < 3; c++ ){
- frame.at<cv::Vec3b>(y,x)[c] = cv::saturate_cast<uchar>( alpha*( frame.at<cv::Vec3b>(y,x)[c] ) + beta );
- }
- }
- }
- }
-
- CaptureImagePtr cap = std::make_shared<CaptureImage>(ts, sen_cam, frame);
- // cap->setType(argv[input]); // only for problem->print() to show img filename
- cap->setName(argv[input]);
- WOLF_DEBUG("Processing image...", path);
- sen->process(cap);
-
- if (IMAGE_OUTPUT){
- cv::namedWindow( cap->getName(), cv::WINDOW_NORMAL );// Create a window for display.
- }
-
- }
- else
- WOLF_WARN("could not load image ", path);
-
- ts += dt;
- }
-
-
- if (IMAGE_OUTPUT){
- WOLF_INFO( "==================== Draw all detections ======================" )
- for (auto F : problem->getTrajectory()->getFrameList())
- {
- if (F->isKey())
- {
- for (auto cap : F->getCaptureList())
- {
- if (cap->getType() == "IMAGE")
- {
- auto img = std::static_pointer_cast<CaptureImage>(cap);
- for (FeatureBasePtr f : img->getFeatureList())
- {
- FeatureApriltagPtr fa = std::static_pointer_cast<FeatureApriltag>(f);
- draw_apriltag(img->getImage(), fa->getTagCorners(), 1);
- }
- cv::imshow( img->getName(), img->getImage() ); // display original image.
- cv::waitKey(1);
- }
- }
- }
- }
- }
-
-
-
-// WOLF_INFO( "==================== Provide perturbed prior ======================" )
-// for (auto kf : problem->getTrajectory()->getFrameList())
-// {
-// Vector7s x;
-// if (kf->isKey())
-// {
-// x.setRandom();
-// x.tail(4).normalize();
-// kf->setState(x);
-// }
-// }
-
- WOLF_INFO( "==================== Solve problem ======================" )
- std::string report = ceres_manager->solve(SolverManager::ReportVerbosity::FULL); // 0: nothing, 1: BriefReport, 2: FullReport
- WOLF_DEBUG(report);
- problem->print(3,0,1,1);
-
-
-
- WOLF_INFO("============= SOLVED PROBLEM : POS | EULER (DEG) ===============")
- for (auto kf : problem->getTrajectory()->getFrameList())
- {
- if (kf->isKey())
- for (auto cap : kf->getCaptureList())
- {
- if (cap->getType() != "POSE")
- {
- Vector3s T = kf->getP()->getState();
- Vector4s qv= kf->getO()->getState();
- Vector3s e = M_TODEG * R2e(q2R(qv));
- WOLF_DEBUG("KF", kf->id(), " => ", T.transpose(), " | ", e.transpose());
- }
- }
- }
- for (auto lmk : problem->getMap()->getLandmarkList())
- {
- Vector3s T = lmk->getP()->getState();
- Vector4s qv= lmk->getO()->getState();
- Vector3s e = M_TODEG * R2e(q2R(qv));
- WOLF_DEBUG(" L", lmk->id(), " => ", T.transpose(), " | ", e.transpose());
- }
-
-
- // ===============================================
- // COVARIANCES ===================================
- // ===============================================
- // Print COVARIANCES of all states
- WOLF_INFO("======== COVARIANCES OF SOLVED PROBLEM : POS | QUAT =======")
- ceres_manager->computeCovariances(SolverManager::CovarianceBlocksToBeComputed::ALL_MARGINALS);
- for (auto kf : problem->getTrajectory()->getFrameList())
- if (kf->isKey())
- {
- Eigen::MatrixXs cov = kf->getCovariance();
- WOLF_DEBUG("KF", kf->id(), "_std (sigmas) = ", cov.diagonal().transpose().array().sqrt());
- }
- for (auto lmk : problem->getMap()->getLandmarkList())
- {
- Eigen::MatrixXs cov = lmk->getCovariance();
- WOLF_DEBUG(" L", lmk->id(), "_std (sigmas) = ", cov.diagonal().transpose().array().sqrt());
- }
- std::cout << std::endl;
-
-
- // ===============================================
- // SAVE MAP TO YAML ==============================
- // ===============================================
- //
- // problem->saveMap(wolf_root + "/src/examples/map_apriltag_set3_HC.yaml", "set3");
-
- if (IMAGE_OUTPUT){
- cv::waitKey(0);
- cv::destroyAllWindows();
- }
-
- return 0;
-
-}
-
-
-void draw_apriltag(cv::Mat image, std::vector<cv::Point2d> corners,
- int thickness, bool draw_corners) {
- cv::line(image, corners[0], corners[1], CV_RGB(255, 0, 0), thickness);
- cv::line(image, corners[1], corners[2], CV_RGB(0, 255, 0), thickness);
- cv::line(image, corners[2], corners[3], CV_RGB(0, 0, 255), thickness);
- cv::line(image, corners[3], corners[0], CV_RGB(255, 0, 255), thickness);
-
- ///////
- // Leads to implement other displays
- ///////
-
-// const auto line_type = cv::LINE_AA;
-// if (draw_corners) {
-// int r = thickness;
-// cv::circle(image, cv::Point2i(p[0].x, p[0].y), r, CV_RGB(255, 0, 0), -1,
-// line_type);
-// cv::circle(image, cv::Point2i(p[1].x, p[1].y), r, CV_RGB(0, 255, 0), -1,
-// line_type);
-// cv::circle(image, cv::Point2i(p[2].x, p[2].y), r, CV_RGB(0, 0, 255), -1,
-// line_type);
-// cv::circle(image, cv::Point2i(p[3].x, p[3].y), r, CV_RGB(255, 0, 255), -1,
-// line_type);
-// }
-
-// cv::putText(image, std::to_string(apriltag.id),
-// cv::Point2f(apriltag.center.x - 5, apriltag.center.y + 5),
-// cv::FONT_HERSHEY_SIMPLEX, 1, CV_RGB(255, 0, 255), 2, line_type);
-
-
-}
-
-//void DrawApriltags(cv::Mat &image, const ApriltagVec &apriltags) {
-// for (const auto &apriltag : apriltags) {
-//// DrawApriltag(image, apriltag);
-// DrawApriltag(image, apriltag, 1);
-// }
-//}
-
diff --git a/demos/demo_autodiff.cpp b/demos/demo_autodiff.cpp
deleted file mode 100644
index 6fa1e01ed..000000000
--- a/demos/demo_autodiff.cpp
+++ /dev/null
@@ -1,422 +0,0 @@
-//std includes
-#include <cstdlib>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// Eigen includes
-#include <eigen3/Eigen/Dense>
-#include <eigen3/Eigen/Geometry>
-
-//Ceres includes
-#include "glog/logging.h"
-
-//Wolf includes
-#include "wolf_manager.h"
-#include "core/sensor/sensor_laser_2D.h"
-#include "core/ceres_wrapper/ceres_manager.h"
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-//faramotics includes
-#include "faramotics/dynamicSceneRender.h"
-#include "faramotics/rangeScan2D.h"
-#include "btr-headers/pose3d.h"
-
-//laser_scan_utils
-#include "iri-algorithms/laser_scan_utils/corner_detector.h"
-#include "iri-algorithms/laser_scan_utils/entities.h"
-
-namespace wolf {
-//function travel around
-void motionCampus(unsigned int ii, Cpose3d & pose, double& displacement_, double& rotation_)
-{
- if (ii <= 120){ displacement_ = 0.1; rotation_ = 0; }
- else if (ii <= 170) { displacement_ = 0.2; rotation_ = 1.8 * M_PI / 180; }
- else if (ii <= 220) { displacement_ = 0; rotation_ =-1.8 * M_PI / 180; }
- else if (ii <= 310) { displacement_ = 0.1; rotation_ = 0; }
- else if (ii <= 487) { displacement_ = 0.1; rotation_ =-1.0 * M_PI / 180; }
- else if (ii <= 600) { displacement_ = 0.2; rotation_ = 0; }
- else if (ii <= 700) { displacement_ = 0.1; rotation_ =-1.0 * M_PI / 180; }
- else if (ii <= 780) { displacement_ = 0; rotation_ =-1.0 * M_PI / 180; }
- else { displacement_ = 0.3; rotation_ = 0; }
-
- pose.moveForward(displacement_);
- pose.rt.setEuler(pose.rt.head() + rotation_, pose.rt.pitch(), pose.rt.roll());
-}
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- std::cout << "\n ========= 2D Robot with odometry and 2 LIDARs ===========\n";
-
- // USER INPUT ============================================================================================
- if (argc != 3 || atoi(argv[1]) < 1 || atoi(argv[2]) < 1 )
- {
- std::cout << "Please call me with: [./test_ceres_manager NI PRINT], where:" << std::endl;
- std::cout << " - NI is the number of iterations (NI > 0)" << std::endl;
- std::cout << " - WS is the window size (WS > 0)" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
-
- unsigned int n_execution = (unsigned int) atoi(argv[1]); //number of iterations of the whole execution
- unsigned int window_size = (unsigned int) atoi(argv[2]);
-
- // INITIALIZATION ============================================================================================
- //init random generators
- Scalar odom_std_factor = 0.5;
- Scalar gps_std = 1;
- std::default_random_engine generator(1);
- std::normal_distribution<Scalar> distribution_odom(0.0, odom_std_factor); //odometry noise
- std::normal_distribution<Scalar> distribution_gps(0.0, gps_std); //GPS noise
-
- //init google log
- //google::InitGoogleLogging(argv[0]);
-
- // Faramotics stuff
- Cpose3d viewPoint, devicePose, laser1Pose, laser2Pose, estimated_vehicle_pose, estimated_laser_1_pose, estimated_laser_2_pose;
- vector < Cpose3d > devicePoses;
- vector<float> scan1, scan2;
- string modelFileName;
-
- //model and initial view point
- modelFileName = "/home/jvallve/iri-lab/faramotics/models/campusNordUPC.obj";
- //modelFileName = "/home/acoromin/dev/br/faramotics/models/campusNordUPC.obj";
- //modelFileName = "/home/andreu/dev/faramotics/models/campusNordUPC.obj";
- devicePose.setPose(2, 8, 0.2, 0, 0, 0);
- viewPoint.setPose(devicePose);
- viewPoint.moveForward(10);
- viewPoint.rt.setEuler(viewPoint.rt.head() + M_PI / 2, viewPoint.rt.pitch() + 30. * M_PI / 180., viewPoint.rt.roll());
- viewPoint.moveForward(-15);
- //glut initialization
- faramotics::initGLUT(argc, argv);
-
- //create a viewer for the 3D model and scan points
- CdynamicSceneRender* myRender = new CdynamicSceneRender(1200, 700, 90 * M_PI / 180, 90 * 700.0 * M_PI / (1200.0 * 180.0), 0.2, 100);
- myRender->loadAssimpModel(modelFileName, true); //with wireframe
- //create scanner and load 3D model
- CrangeScan2D* myScanner = new CrangeScan2D(HOKUYO_UTM30LX_180DEG); //HOKUYO_UTM30LX_180DEG or LEUZE_RS4
- myScanner->loadAssimpModel(modelFileName);
-
- //variables
- Eigen::Vector3s odom_reading;
- Eigen::Vector2s gps_fix_reading;
- Eigen::VectorXs pose_odom(3); //current odometry integred pose
- Eigen::VectorXs ground_truth(n_execution * 3); //all true poses
- Eigen::VectorXs odom_trajectory(n_execution * 3); //open loop trajectory
- Eigen::VectorXs mean_times = Eigen::VectorXs::Zero(7);
- clock_t t1, t2;
-
- // Wolf manager initialization
- Eigen::Vector3s odom_pose = Eigen::Vector3s::Zero();
- Eigen::Vector3s gps_pose = Eigen::Vector3s::Zero();
- Eigen::Vector4s laser_1_pose, laser_2_pose; //xyz + theta
- laser_1_pose << 1.2, 0, 0, 0; //laser 1
- laser_2_pose << -1.2, 0, 0, M_PI; //laser 2
- SensorOdom2D odom_sensor(std::make_shared<StateBlock>(odom_pose.head(2)), std::make_shared<StateBlock>(odom_pose.tail(1)), odom_std_factor, odom_std_factor);
- SensorGPSFix gps_sensor(std::make_shared<StateBlock>(gps_pose.head(2)), std::make_shared<StateBlock>(gps_pose.tail(1)), gps_std);
- SensorLaser2D laser_1_sensor(std::make_shared<StateBlock>(laser_1_pose.head(2)), std::make_shared<StateBlock>(laser_1_pose.tail(1)));
- SensorLaser2D laser_2_sensor(std::make_shared<StateBlock>(laser_2_pose.head(2)), std::make_shared<StateBlock>(laser_2_pose.tail(1)));
- laser_1_sensor.addProcessor(new ProcessorLaser2D());
- laser_2_sensor.addProcessor(new ProcessorLaser2D());
-
- // Initial pose
- pose_odom << 2, 8, 0;
- ground_truth.head(3) = pose_odom;
- odom_trajectory.head(3) = pose_odom;
-
- WolfManager* wolf_manager_ceres = new WolfManager(FRM_PO_2D, &odom_sensor, pose_odom, Eigen::Matrix3s::Identity() * 0.01, window_size, 0.3);
- WolfManager* wolf_manager_wolf = new WolfManager(FRM_PO_2D, &odom_sensor, pose_odom, Eigen::Matrix3s::Identity() * 0.01, window_size, 0.3);
-
- // Ceres wrapper
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- // ceres_options.minimizer_progress_to_stdout = false;
- // ceres_options.line_search_direction_type = ceres::LBFGS;
- // ceres_options.max_num_iterations = 100;
- CeresManager* ceres_manager_ceres = new CeresManager(wolf_manager_ceres->getProblem(), false);
- CeresManager* ceres_manager_wolf = new CeresManager(wolf_manager_wolf->getProblem(), true);
- std::ofstream log_file, landmark_file; //output file
-
- //std::cout << "START TRAJECTORY..." << std::endl;
- // START TRAJECTORY ============================================================================================
- for (unsigned int step = 1; step < n_execution; step++)
- {
- //get init time
- t2 = clock();
-
- // ROBOT MOVEMENT ---------------------------
- //std::cout << "ROBOT MOVEMENT..." << std::endl;
- // moves the device position
- t1 = clock();
- motionCampus(step, devicePose, odom_reading(0), odom_reading(2));
- odom_reading(1) = 0;
- devicePoses.push_back(devicePose);
-
- // SENSOR DATA ---------------------------
- //std::cout << "SENSOR DATA..." << std::endl;
- // store groundtruth
- ground_truth.segment(step * 3, 3) << devicePose.pt(0), devicePose.pt(1), devicePose.rt.head();
-
- // compute odometry
- odom_reading(0) += distribution_odom(generator) * (odom_reading(0) == 0 ? 1e-6 : odom_reading(0));
- odom_reading(1) += distribution_odom(generator) * 1e-6;
- odom_reading(2) += distribution_odom(generator) * (odom_reading(2) == 0 ? 1e-6 : odom_reading(2));
-
- // odometry integration
- pose_odom(0) = pose_odom(0) + odom_reading(0) * cos(pose_odom(2)) - odom_reading(1) * sin(pose_odom(2));
- pose_odom(1) = pose_odom(1) + odom_reading(0) * sin(pose_odom(2)) + odom_reading(1) * cos(pose_odom(2));
- pose_odom(2) = pose_odom(2) + odom_reading(1);
- odom_trajectory.segment(step * 3, 3) = pose_odom;
-
- // compute GPS
- gps_fix_reading << devicePose.pt(0), devicePose.pt(1);
- gps_fix_reading(0) += distribution_gps(generator);
- gps_fix_reading(1) += distribution_gps(generator);
-
- //compute scans
- scan1.clear();
- scan2.clear();
- // scan 1
- laser1Pose.setPose(devicePose);
- laser1Pose.moveForward(laser_1_pose(0));
- myScanner->computeScan(laser1Pose, scan1);
- // scan 2
- laser2Pose.setPose(devicePose);
- laser2Pose.moveForward(laser_2_pose(0));
- laser2Pose.rt.setEuler(laser2Pose.rt.head() + M_PI, laser2Pose.rt.pitch(), laser2Pose.rt.roll());
- myScanner->computeScan(laser2Pose, scan2);
-
- mean_times(0) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // ADD CAPTURES ---------------------------
- std::cout << "ADD CAPTURES..." << std::endl;
- t1 = clock();
- // adding new sensor captures
- wolf_manager_ceres->addCapture(new CaptureOdom2D(TimeStamp(),TimeStamp(), &odom_sensor, odom_reading)); //, odom_std_factor * Eigen::MatrixXs::Identity(2,2)));
- wolf_manager_ceres->addCapture(new CaptureGPSFix(TimeStamp(), &gps_sensor, gps_fix_reading, gps_std * Eigen::MatrixXs::Identity(3,3)));
- wolf_manager_ceres->addCapture(new CaptureLaser2D(TimeStamp(), &laser_1_sensor, scan1));
- wolf_manager_ceres->addCapture(new CaptureLaser2D(TimeStamp(), &laser_2_sensor, scan2));
- wolf_manager_wolf->addCapture(new CaptureOdom2D(TimeStamp(),TimeStamp(), &odom_sensor, odom_reading)); //, odom_std_factor * Eigen::MatrixXs::Identity(2,2)));
- wolf_manager_wolf->addCapture(new CaptureGPSFix(TimeStamp(), &gps_sensor, gps_fix_reading, gps_std * Eigen::MatrixXs::Identity(3,3)));
- wolf_manager_wolf->addCapture(new CaptureLaser2D(TimeStamp(), &laser_1_sensor, scan1));
- wolf_manager_wolf->addCapture(new CaptureLaser2D(TimeStamp(), &laser_2_sensor, scan2));
-
- // updating problem
- wolf_manager_ceres->update();
- wolf_manager_wolf->update();
- mean_times(1) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // UPDATING CERES ---------------------------
- std::cout << "UPDATING CERES..." << std::endl;
- t1 = clock();
- // update state units and factors in ceres
- ceres_manager_ceres->update();
- ceres_manager_wolf->update();
- mean_times(2) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // SOLVE OPTIMIZATION ---------------------------
- std::cout << "SOLVING..." << std::endl;
- t1 = clock();
- ceres::Solver::Summary summary_ceres = ceres_manager_ceres->solve(ceres_options);
- ceres::Solver::Summary summary_wolf = ceres_manager_wolf->solve(ceres_options);
- std::cout << "CERES AUTO DIFF" << std::endl;
- std::cout << "Jacobian evaluation: " << summary_ceres.jacobian_evaluation_time_in_seconds << std::endl;
- std::cout << "Total time: " << summary_ceres.total_time_in_seconds << std::endl;
- std::cout << "WOLF AUTO DIFF" << std::endl;
- std::cout << "Jacobian evaluation: " << summary_wolf.jacobian_evaluation_time_in_seconds << std::endl;
- std::cout << "Total time: " << summary_wolf.total_time_in_seconds << std::endl;
- mean_times(3) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- std::cout << "CERES AUTO DIFF solution:" << std::endl;
- std::cout << wolf_manager_ceres->getVehiclePose().transpose() << std::endl;
- std::cout << "WOLF AUTO DIFF solution:" << std::endl;
- std::cout << wolf_manager_wolf->getVehiclePose().transpose() << std::endl;
-
- // COMPUTE COVARIANCES ---------------------------
- std::cout << "COMPUTING COVARIANCES..." << std::endl;
- t1 = clock();
- ceres_manager_ceres->computeCovariances(ALL_MARGINALS);
- ceres_manager_wolf->computeCovariances(ALL_MARGINALS);
- Eigen::MatrixXs marginal_ceres(3,3), marginal_wolf(3,3);
- wolf_manager_ceres->getProblem()->getCovarianceBlock(wolf_manager_ceres->getProblem()->getTrajectory()->getLastFrame()->getP(),
- wolf_manager_ceres->getProblem()->getTrajectory()->getLastFrame()->getP(),
- marginal_ceres, 0, 0);
- wolf_manager_ceres->getProblem()->getCovarianceBlock(wolf_manager_ceres->getProblem()->getTrajectory()->getLastFrame()->getP(),
- wolf_manager_ceres->getProblem()->getTrajectory()->getLastFrame()->getO(),
- marginal_ceres, 0, 2);
- wolf_manager_ceres->getProblem()->getCovarianceBlock(wolf_manager_ceres->getProblem()->getTrajectory()->getLastFrame()->getO(),
- wolf_manager_ceres->getProblem()->getTrajectory()->getLastFrame()->getO(),
- marginal_ceres, 2, 2);
- wolf_manager_wolf->getProblem()->getCovarianceBlock(wolf_manager_wolf->getProblem()->getTrajectory()->getLastFrame()->getP(),
- wolf_manager_wolf->getProblem()->getTrajectory()->getLastFrame()->getP(),
- marginal_wolf, 0, 0);
- wolf_manager_wolf->getProblem()->getCovarianceBlock(wolf_manager_wolf->getProblem()->getTrajectory()->getLastFrame()->getP(),
- wolf_manager_wolf->getProblem()->getTrajectory()->getLastFrame()->getO(),
- marginal_wolf, 0, 2);
- wolf_manager_wolf->getProblem()->getCovarianceBlock(wolf_manager_wolf->getProblem()->getTrajectory()->getLastFrame()->getO(),
- wolf_manager_wolf->getProblem()->getTrajectory()->getLastFrame()->getO(),
- marginal_wolf, 2, 2);
- std::cout << "CERES AUTO DIFF covariance:" << std::endl;
- std::cout << marginal_ceres << std::endl;
- std::cout << "WOLF AUTO DIFF covariance:" << std::endl;
- std::cout << marginal_wolf << std::endl;
- mean_times(4) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // DRAWING STUFF ---------------------------
- t1 = clock();
- // draw detected corners
-// std::list < laserscanutils::Corner > corner_list;
-// std::vector<double> corner_vector;
-// CaptureLaser2D last_scan(TimeStamp(), &laser_1_sensor, scan1);
-// last_scan.extractCorners(corner_list);
-// for (std::list<laserscanutils::Corner>::iterator corner_it = corner_list.begin(); corner_it != corner_list.end(); corner_it++)
-// {
-// corner_vector.push_back(corner_it->pt_(0));
-// corner_vector.push_back(corner_it->pt_(1));
-// }
-// myRender->drawCorners(laser1Pose, corner_vector);
-
-// // draw landmarks
-// std::vector<double> landmark_vector;
-// for (auto landmark_it = wolf_manager->getProblem()->getMap()->getLandmarkList().begin(); landmark_it != wolf_manager->getProblem()->getMap()->getLandmarkList().end(); landmark_it++)
-// {
-// Scalar* position_ptr = (*landmark_it)->getP()->get();
-// landmark_vector.push_back(*position_ptr); //x
-// landmark_vector.push_back(*(position_ptr + 1)); //y
-// landmark_vector.push_back(0.2); //z
-// }
-// myRender->drawLandmarks(landmark_vector);
-//
-// // draw localization and sensors
-// estimated_vehicle_pose.setPose(wolf_manager->getVehiclePose()(0), wolf_manager->getVehiclePose()(1), 0.2, wolf_manager->getVehiclePose()(2), 0, 0);
-// estimated_laser_1_pose.setPose(estimated_vehicle_pose);
-// estimated_laser_1_pose.moveForward(laser_1_pose(0));
-// estimated_laser_2_pose.setPose(estimated_vehicle_pose);
-// estimated_laser_2_pose.moveForward(laser_2_pose(0));
-// estimated_laser_2_pose.rt.setEuler(estimated_laser_2_pose.rt.head() + M_PI, estimated_laser_2_pose.rt.pitch(), estimated_laser_2_pose.rt.roll());
-// myRender->drawPoseAxisVector( { estimated_vehicle_pose, estimated_laser_1_pose, estimated_laser_2_pose });
-//
-// //Set view point and render the scene
-// //locate visualization view point, somewhere behind the device
-//// viewPoint.setPose(devicePose);
-//// viewPoint.rt.setEuler( viewPoint.rt.head(), viewPoint.rt.pitch()+20.*M_PI/180., viewPoint.rt.roll() );
-//// viewPoint.moveForward(-5);
-// myRender->setViewPoint(viewPoint);
-// myRender->drawPoseAxis(devicePose);
-// myRender->drawScan(laser1Pose, scan1, 180. * M_PI / 180., 90. * M_PI / 180.); //draw scan
-// myRender->render();
-// mean_times(5) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // TIME MANAGEMENT ---------------------------
- double dt = ((double) clock() - t2) / CLOCKS_PER_SEC;
- mean_times(6) += dt;
- if (dt < 0.1)
- usleep(100000 - 1e6 * dt);
-
-// std::cout << "\nTree after step..." << std::endl;
- }
-
- // DISPLAY RESULTS ============================================================================================
- mean_times /= n_execution;
- std::cout << "\nSIMULATION AVERAGE LOOP DURATION [s]" << std::endl;
- std::cout << " data generation: " << mean_times(0) << std::endl;
- std::cout << " wolf managing: " << mean_times(1) << std::endl;
- std::cout << " ceres managing: " << mean_times(2) << std::endl;
- std::cout << " ceres optimization: " << mean_times(3) << std::endl;
- std::cout << " ceres covariance: " << mean_times(4) << std::endl;
- std::cout << " results drawing: " << mean_times(5) << std::endl;
- std::cout << " loop time: " << mean_times(6) << std::endl;
-
-// std::cout << "\nTree before deleting..." << std::endl;
-
-// // Draw Final result -------------------------
-// std::vector<double> landmark_vector;
-// for (auto landmark_it = wolf_manager->getProblem()->getMap()->getLandmarkList().begin(); landmark_it != wolf_manager->getProblem()->getMap()->getLandmarkList().end(); landmark_it++)
-// {
-// Scalar* position_ptr = (*landmark_it)->getP()->get();
-// landmark_vector.push_back(*position_ptr); //x
-// landmark_vector.push_back(*(position_ptr + 1)); //y
-// landmark_vector.push_back(0.2); //z
-// }
-// myRender->drawLandmarks(landmark_vector);
-//// viewPoint.setPose(devicePoses.front());
-//// viewPoint.moveForward(10);
-//// viewPoint.rt.setEuler( viewPoint.rt.head()+M_PI/4, viewPoint.rt.pitch()+20.*M_PI/180., viewPoint.rt.roll() );
-//// viewPoint.moveForward(-10);
-// myRender->setViewPoint(viewPoint);
-// myRender->render();
-
- // Print Final result in a file -------------------------
- // Vehicle poses
-// int i = 0;
-// Eigen::VectorXs state_poses(n_execution * 3);
-// for (auto frame_it = wolf_manager->getProblem()->getTrajectory()->getFrameList().begin(); frame_it != wolf_manager->getProblem()->getTrajectory()->getFrameList().end(); frame_it++)
-// {
-// state_poses.segment(i, 3) << *(*frame_it)->getP()->get(), *((*frame_it)->getP()->get() + 1), *(*frame_it)->getO()->get();
-// i += 3;
-// }
-//
-// // Landmarks
-// i = 0;
-// Eigen::VectorXs landmarks(wolf_manager->getProblem()->getMap()->getLandmarkList().size() * 2);
-// for (auto landmark_it = wolf_manager->getProblem()->getMap()->getLandmarkList().begin(); landmark_it != wolf_manager->getProblem()->getMap()->getLandmarkList().end(); landmark_it++)
-// {
-// Eigen::Map<Eigen::Vector2s> landmark((*landmark_it)->getP()->get());
-// landmarks.segment(i, 2) = landmark;
-// i += 2;
-// }
-//
-// // Print log files
-// std::string filepath = getenv("HOME") + std::string("/Desktop/log_file_2.txt");
-// log_file.open(filepath, std::ofstream::out); //open log file
-//
-// if (log_file.is_open())
-// {
-// log_file << 0 << std::endl;
-// for (unsigned int ii = 0; ii < n_execution; ii++)
-// log_file << state_poses.segment(ii * 3, 3).transpose() << "\t" << ground_truth.segment(ii * 3, 3).transpose() << "\t" << (state_poses.segment(ii * 3, 3) - ground_truth.segment(ii * 3, 3)).transpose() << "\t" << odom_trajectory.segment(ii * 3, 3).transpose() << std::endl;
-// log_file.close(); //close log file
-// std::cout << std::endl << "Result file " << filepath << std::endl;
-// }
-// else
-// std::cout << std::endl << "Failed to write the log file " << filepath << std::endl;
-//
-// std::string filepath2 = getenv("HOME") + std::string("/Desktop/landmarks_file_2.txt");
-// landmark_file.open(filepath2, std::ofstream::out); //open log file
-//
-// if (landmark_file.is_open())
-// {
-// for (unsigned int ii = 0; ii < landmarks.size(); ii += 2)
-// landmark_file << landmarks.segment(ii, 2).transpose() << std::endl;
-// landmark_file.close(); //close log file
-// std::cout << std::endl << "Landmark file " << filepath << std::endl;
-// }
-// else
-// std::cout << std::endl << "Failed to write the landmark file " << filepath << std::endl;
-//
-// std::cout << "Press any key for ending... " << std::endl << std::endl;
-// std::getchar();
-
- delete myRender;
- delete myScanner;
- delete wolf_manager_ceres;
- delete wolf_manager_wolf;
- std::cout << "wolf deleted" << std::endl;
- delete ceres_manager_ceres;
- delete ceres_manager_wolf;
- std::cout << "ceres_manager deleted" << std::endl;
-
- std::cout << " ========= END ===========" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_capture_laser_2D.cpp b/demos/demo_capture_laser_2D.cpp
deleted file mode 100644
index cd5e40239..000000000
--- a/demos/demo_capture_laser_2D.cpp
+++ /dev/null
@@ -1,134 +0,0 @@
-
-//std
-#include <random>
-
-//wolf
-#include "core/capture/capture_laser_2D.h"
-
-// Eigen in std vector
-#include <Eigen/StdVector>
-
-//main
-int main(int argc, char *argv[])
-{
- using namespace wolf;
-
- std::cout << std::endl << "CaptureLaser2D class test" << std::endl;
- std::cout << "========================================================" << std::endl;
-
- //scan ranges
- Eigen::VectorXs ranges(720);
- ranges << 2.78886,2.78289,2.7832,2.78367,2.7843,2.78508,2.78603,2.78713,2.78839,2.78981,
- 2.79139,2.78669,2.78855,2.79057,2.79274,2.79507,2.79098,2.79359,2.79635,2.79927,
- 2.79566,2.79886,2.80221,2.79895,2.80258,2.80638,2.80345,2.80753,2.81176,2.80917,
- 2.81368,2.81132,2.81611,2.81396,2.81903,2.73664,2.72743,2.71782,2.70883,2.69945,
- 2.69067,2.6815,2.67294,2.66398,2.65562,2.64736,2.6387,2.63064,2.62218,2.61431,
- 2.60605,2.59837,2.59078,2.5828,2.57539,2.56759,2.56036,2.55321,2.54568,2.53871,
- 2.53182,2.52455,2.51782,2.51118,2.50415,2.49767,2.49127,2.48495,2.47824,2.47207,
- 2.46597,2.4595,2.45355,2.44768,2.44188,2.4357,2.43005,2.42446,2.41894,2.4135,
- 2.40768,2.40236,2.39712,2.39195,2.3864,2.38135,2.37637,2.37146,2.36661,2.36182,
- 2.35666,2.352,2.3474,2.34286,2.34186,2.36289,2.41051,2.43311,2.45628,2.48003,
- 2.50439,2.52937,2.555,2.61224,2.63993,2.66837,2.69757,2.72758,2.75841,2.79011,
- 2.82269,2.85621,2.8907,2.96659,3.0042,3.04295,3.08289,3.12406,3.16652,3.21033,
- 3.22693,3.23444,3.24207,3.24982,3.2577,3.26571,3.2855,3.29383,3.30229,3.31088,
- 3.3196,3.32846,3.33745,3.34658,3.35584,3.36524,3.37478,3.38445,3.39427,3.40423,
- 3.41434,3.42459,3.43499,3.44553,3.45623,3.46707,3.47807,3.48923,3.50053,3.512,
- 3.52362,3.53541,3.54736,3.55947,3.57175,3.5842,3.59681,3.6096,3.62256,3.63569,
- 3.64901,3.6625,3.67617,3.69003,3.70407,3.7183,3.73272,3.74733,3.76214,3.7931,
- 3.80843,3.82397,3.83972,3.85567,3.87183,3.88822,3.90481,3.92163,3.93867,3.95593,
- 3.97343,3.97347,3.99127,4.00931,4.02758,4.0461,4.06486,4.08387,4.10314,4.12266,
- 4.14244,4.16248,4.20237,4.22313,4.24418,4.26551,4.28712,4.30903,4.33122,4.35372,
- 4.37652,4.39963,4.42304,4.44678,4.47084,4.49523,4.51994,4.545,4.57041,4.59615,
- 4.62225,4.64871,4.67554,4.70274,4.73032,4.75828,4.78663,4.81538,4.84452,4.8741,
- 4.90409,4.9345,4.96534,4.99662,5.02836,5.06053,5.09317,5.12628,5.15987,5.19395,
- 5.22853,5.2636,5.2992,5.33532,5.37197,5.44106,5.47923,5.51796,5.55729,5.59721,
- 5.63773,5.67888,5.72066,5.76307,5.80615,5.8499,5.89432,5.93945,6.02374,6.07085,
- 6.11872,6.16734,6.21676,6.26698,6.318,6.36987,6.42258,6.47618,6.5758,6.6319,
- 6.68894,6.74694,6.80593,6.86593,6.92698,7.04022,7.10425,7.1694,7.23572,7.30322,
- 7.37192,7.49928,7.57149,7.64505,7.58372,7.51951,7.45681,7.32129,7.32938,7.34276,
- 7.35632,7.36877,7.38272,7.39687,7.41124,7.4258,7.43923,7.4542,7.46937,7.48477,
- 7.49904,7.51485,7.53087,7.54579,7.56225,7.57894,7.59587,7.61164,7.62902,8.37389,
- 8.39194,8.41173,8.43177,8.45059,8.47118,8.49202,8.51164,8.53305,8.55319,8.57516,
- 8.59739,8.61839,8.64122,8.6628,8.6862,8.70837,8.73237,8.7567,8.77979,8.80472,
- 8.82843,8.85402,8.87835,8.9046,8.9296,8.9565,8.98218,9.0082,9.03616,9.06287,
- 9.09152,9.11895,9.14834,9.17652,9.20503,9.23557,9.26487,9.29454,9.32626,9.35674,
- 9.38762,9.42055,9.45226,9.4844,9.51695,9.55162,9.58503,9.61893,9.65324,4.38929,
- 4.38536,4.36058,4.3365,4.3131,4.29036,4.26827,4.24682,4.22598,4.20576,4.18612,
- 4.1944,4.17582,4.15708,4.13859,4.12032,4.10229,4.08449,4.06691,4.04955,4.03241,
- 4.01549,3.99916,3.98265,3.96634,3.95024,3.93434,3.91901,3.90349,3.88817,3.87304,
- 3.85845,3.84368,3.82909,3.81504,3.80081,3.78674,3.7732,3.75948,3.74591,3.73287,
- 3.71963,3.7069,3.69398,3.68156,3.66894,3.65647,3.6445,3.63233,3.62065,3.60876,
- 3.59736,3.58576,3.58265,3.61553,3.62696,3.63867,3.67347,3.68596,3.72229,3.7356,
- 3.77355,3.78772,3.80219,3.84244,3.85785,3.89993,3.9163,3.93303,3.97774,3.99551,
- 4.01367,4.06121,4.0805,4.10019,4.15081,4.17174,4.19309,13.8062,13.7714,13.7384,
- 13.7075,13.8936,13.9735,14.0549,14.1382,14.3407,15.8017,15.9009,16.002,16.1054,
- 16.3519,16.462,16.5744,16.6893,16.9594,17.0819,17.2072,17.3352,17.4661,17.6,
- 8.14878,8.1334,8.11823,8.10324,8.08848,8.07391,8.0588,8.04465,8.03069,8.01693,
- 8.00338,7.99,7.97684,7.96312,7.95032,7.93773,7.92533,7.91309,7.90106,7.88922,7.87755,
- 7.86606,7.85476,7.84289,7.83195,7.82116,7.81058,7.80017,7.78993,7.77984,7.76995,
- 7.76021,7.75066,7.74128,7.73204,7.76034,7.99805,8.11853,8.24311,8.37202,12.3718,
- 12.3587,12.346,12.3336,12.3213,12.3094,12.2976,12.2862,12.275,12.264,12.2534,12.2429,
- 12.2327,12.2228,12.213,12.2036,12.1944,12.1854,12.1766,12.3577,12.667,16.7608,16.7501,
- 16.7398,16.7297,16.7201,16.7106,16.7015,16.6929,16.6844,16.9488,20.069,20.0619,20.0552,
- 20.0489,20.043,20.0374,20.0323,20.0275,20.0231,20.0191,20.0155,20.0122,20.0094,20.0069,
- 20.0048,20.0031,20.0018,20.0008,20.0002,20.0001,20.0002,20.0008,20.0018,20.0031,20.0048,
- 20.0069,20.0094,20.0122,20.0155,20.0191,20.0231,20.0275,20.0323,20.0374,20.043,20.0489,
- 20.0552,20.0619,20.069,20.0764,20.0843,20.0926,20.1012,20.1102,20.1196,20.1294,20.1397,
- 20.1502,20.1612,20.1726,20.1844,20.1966,20.2092,20.2222,20.2356,20.2494,20.2636,20.2782,
- 20.2932,20.3086,20.3244,20.3407,20.3573,20.3744,20.3919,20.4098,20.4281,20.4469,20.466,
- 20.4856,20.5057,20.5261,20.547,20.5684,20.5901,20.6123,20.635,20.6581,20.6816,20.7056,
- 20.73,20.7549,20.7802,20.806,20.8323,20.859,20.8862,20.9139,20.942,20.9706,20.9997,
- 21.0293,21.0594,21.0899,21.1209,21.1525,21.1845,21.217,21.2501,21.2836,21.3177,21.3522,
- 21.3873,21.423,21.4591,21.4958,21.533,21.5707,21.6091,21.6479,21.6873,21.7273,21.7678,
- 21.8089,21.8505,21.8928,21.9356,21.979,22.023,22.0676,22.1128,22.1586,22.2051,22.2521,
- 22.2998,22.3481,22.397,22.4466,22.4968,22.5477,22.5992,22.6515,22.7043,22.7579,22.8122,
- 22.8671,22.9228,22.9792,23.0363,23.0941,23.1526,23.2119,23.2719,23.3327,23.3943,23.4566,
- 23.5197,23.5836,23.6483,23.7138,23.7802,23.8473,23.9153,23.9842,24.0539,24.1244,24.1959,
- 24.2682,24.3414,24.4156,24.4906,24.5666,24.6435,24.7214,24.8003,24.8801,24.9609,25.0428,
- 25.1256,25.2095,25.2944,25.3804,25.4675,25.5556,25.6449,25.7353,25.8268,25.9194,26.0132,
- 26.1082,26.2044,26.3018,26.4004,26.5003,26.6015,26.7039,26.8077,26.9127,27.0191,27.1269,
- 27.2361,27.3466,27.4586,27.572,27.6869,27.8033,27.9213,28.0407,28.1617;
-
- //variable declarations and inits
- Eigen::VectorXs device_pose(6);
- device_pose << 0,0,0,0,0,0; //origin, no rotation
- TimeStamp time_stamp;
- time_stamp.setToNow();
- std::list<Eigen::Vector4s, Eigen::aligned_allocator<Eigen::Vector4s> > corner_list;
-
- //Create Device objects
- //SensorLaser2D device(device_pose, ranges.size(), M_PI, 0.2, 30.0, 0.01);
- SensorLaser2D device(device_pose, -M_PI/2, M_PI/2, M_PI/ranges.size(), 0.2, 30.0, 0.01);
- device.printSensorParameters();
-
- //init a noise generator
- std::default_random_engine generator(1);
- std::normal_distribution<Scalar> distribution_range(0.,device.getRangeStdDev()); //odometry noise
-
- //Create a Capture object
- CaptureLaser2D capture(time_stamp, &device, ranges);
-
- //add noise to measurements
- //TODO
-
- //do things with the measurements
- clock_t t1, t2;
- t1=clock();
- capture.extractCorners(corner_list);
- t2=clock();
- std::cout << "seconds = " << ((double)t2-t1)/CLOCKS_PER_SEC << std::endl;
- capture.createFeatures(corner_list);
- capture.printSelf();
-
- //print corners
- std::cout << "CORNER LIST" << std::endl;
- for (auto corner_it = corner_list.begin(); corner_it != corner_list.end(); corner_it ++ )
- {
- std::cout << corner_it->x() << " , " << corner_it->y() << std::endl;
- }
-
- std::cout << "========================================================" << std::endl;
- std::cout << std::endl << "End CaptureLaser2D class test" << std::endl;
- return 0;
-}
-
diff --git a/demos/demo_ceres_2_lasers.cpp b/demos/demo_ceres_2_lasers.cpp
deleted file mode 100644
index 456367a2c..000000000
--- a/demos/demo_ceres_2_lasers.cpp
+++ /dev/null
@@ -1,420 +0,0 @@
-//std includes
-#include "base/sensor/sensor_GPS_fix.h"
-#include <cstdlib>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// Eigen includes
-#include <eigen3/Eigen/Dense>
-#include <eigen3/Eigen/Geometry>
-
-//Ceres includes
-#include "glog/logging.h"
-
-//Wolf includes
-#include "base/problem/problem.h"
-#include "base/processor/processor_tracker_landmark_corner.h"
-#include "base/processor/processor_odom_2D.h"
-#include "base/sensor/sensor_laser_2D.h"
-#include "base/sensor/sensor_odom_2D.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-
-// laserscanutils
-#include "laser_scan_utils/line_finder_iterative.h"
-#include "laser_scan_utils/laser_scan.h"
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-#include "base/capture/capture_pose.h"
-//faramotics includes
-#include "faramotics/dynamicSceneRender.h"
-#include "faramotics/rangeScan2D.h"
-#include "btr-headers/pose3d.h"
-
-namespace wolf {
-class FaramoticsRobot
-{
- public:
-
- Cpose3d viewPoint, devicePose, laser1Pose, laser2Pose, estimated_vehicle_pose, estimated_laser_1_pose, estimated_laser_2_pose;
- vector < Cpose3d > devicePoses;
- vector<float> scan1, scan2;
- string modelFileName;
- CrangeScan2D* myScanner;
- CdynamicSceneRender* myRender;
- Eigen::Vector3s ground_truth_pose_;
- Eigen::Vector4s laser_1_pose_, laser_2_pose_;
-
- FaramoticsRobot(int argc, char** argv, const Eigen::Vector4s& _laser_1_pose, const Eigen::Vector4s& _laser_2_pose) :
- modelFileName("/home/jvallve/iri-lab/faramotics/models/campusNordUPC.obj"),
- laser_1_pose_(_laser_1_pose),
- laser_2_pose_(_laser_2_pose)
- {
- devicePose.setPose(2, 8, 0.2, 0, 0, 0);
- viewPoint.setPose(devicePose);
- viewPoint.moveForward(10);
- viewPoint.rt.setEuler(viewPoint.rt.head() + M_PI / 2, viewPoint.rt.pitch() + 30. * M_PI / 180., viewPoint.rt.roll());
- viewPoint.moveForward(-15);
- //glut initialization
- faramotics::initGLUT(argc, argv);
- //create a viewer for the 3D model and scan points
- myRender = new CdynamicSceneRender(1200, 700, 90 * M_PI / 180, 90 * 700.0 * M_PI / (1200.0 * 180.0), 0.2, 100);
- myRender->loadAssimpModel(modelFileName, true); //with wireframe
- //create scanner and load 3D model
- myScanner = new CrangeScan2D(HOKUYO_UTM30LX_180DEG); //HOKUYO_UTM30LX_180DEG or LEUZE_RS4
- myScanner->loadAssimpModel(modelFileName);
- }
-
- //function travel around
- Eigen::Vector3s motionCampus(unsigned int ii, double& displacement_, double& rotation_)
- {
- if (ii <= 120){ displacement_ = 0.1; rotation_ = 0; }
- else if (ii <= 170) { displacement_ = 0.2; rotation_ = 1.8 * M_PI / 180; }
- else if (ii <= 220) { displacement_ = 0; rotation_ =-1.8 * M_PI / 180; }
- else if (ii <= 310) { displacement_ = 0.1; rotation_ = 0; }
- else if (ii <= 487) { displacement_ = 0.1; rotation_ =-1.0 * M_PI / 180; }
- else if (ii <= 600) { displacement_ = 0.2; rotation_ = 0; }
- else if (ii <= 700) { displacement_ = 0.1; rotation_ =-1.0 * M_PI / 180; }
- else if (ii <= 780) { displacement_ = 0; rotation_ =-1.0 * M_PI / 180; }
- else { displacement_ = 0.3; rotation_ = 0; }
-
- devicePose.moveForward(displacement_);
- devicePose.rt.setEuler(devicePose.rt.head() + rotation_, devicePose.rt.pitch(), devicePose.rt.roll());
-
- // laser 1
- laser1Pose.setPose(devicePose);
- laser1Pose.moveForward(laser_1_pose_(0));
- // laser 2
- laser2Pose.setPose(devicePose);
- laser2Pose.moveForward(laser_2_pose_(0));
- laser2Pose.rt.setEuler(laser2Pose.rt.head() + laser_2_pose_(3), laser2Pose.rt.pitch(), laser2Pose.rt.roll());
-
- devicePoses.push_back(devicePose);
-
- ground_truth_pose_ << devicePose.pt(0), devicePose.pt(1), devicePose.rt.head();
- return ground_truth_pose_;
- }
-
- ~FaramoticsRobot()
- {
- std::cout << "deleting render and scanner.." << std::endl;
- delete myRender;
- delete myScanner;
- std::cout << "deleted!" << std::endl;
- }
-
- //compute scans
- vector<float> computeScan(const int scan_id)
- {
- if (scan_id == 1)
- {
- scan1.clear();
- myScanner->computeScan(laser1Pose, scan1);
- return scan1;
- }
- else
- {
- scan2.clear();
- myScanner->computeScan(laser2Pose, scan2);
- return scan2;
- }
- }
-
- void render(const FeatureBasePtrList& feature_list, int laser, const LandmarkBasePtrList& landmark_list, const Eigen::Vector3s& estimated_pose)
- {
- // detected corners
- //std::cout << " drawCorners: " << feature_list.size() << std::endl;
- std::vector<double> corner_vector;
- corner_vector.reserve(2*feature_list.size());
- for (auto corner : feature_list)
- {
- //std::cout << " corner " << corner->id() << std::endl;
- corner_vector.push_back(corner->getMeasurement(0));
- corner_vector.push_back(corner->getMeasurement(1));
- }
- myRender->drawCorners(laser == 1 ? laser1Pose : laser2Pose, corner_vector);
-
- // landmarks
- //std::cout << " drawLandmarks: " << landmark_list.size() << std::endl;
- std::vector<double> landmark_vector;
- landmark_vector.reserve(3*landmark_list.size());
- for (auto landmark : landmark_list)
- {
- Scalar* position_ptr = landmark->getP()->get();
- landmark_vector.push_back(*position_ptr); //x
- landmark_vector.push_back(*(position_ptr + 1)); //y
- landmark_vector.push_back(0.2); //z
- }
- myRender->drawLandmarks(landmark_vector);
-
- // draw localization and sensors
- estimated_vehicle_pose.setPose(estimated_pose(0), estimated_pose(1), 0.2, estimated_pose(2), 0, 0);
- estimated_laser_1_pose.setPose(estimated_vehicle_pose);
- estimated_laser_1_pose.moveForward(laser_1_pose_(0));
- estimated_laser_2_pose.setPose(estimated_vehicle_pose);
- estimated_laser_2_pose.moveForward(laser_2_pose_(0));
- estimated_laser_2_pose.rt.setEuler(estimated_laser_2_pose.rt.head() + laser_2_pose_(3), estimated_laser_2_pose.rt.pitch(), estimated_laser_2_pose.rt.roll());
- myRender->drawPoseAxisVector( { estimated_vehicle_pose, estimated_laser_1_pose, estimated_laser_2_pose });
-
- //Set view point and render the scene
- //locate visualization view point, somewhere behind the device
- // viewPoint.setPose(devicePose);
- // viewPoint.rt.setEuler( viewPoint.rt.head(), viewPoint.rt.pitch()+20.*M_PI/180., viewPoint.rt.roll() );
- // viewPoint.moveForward(-5);
- myRender->setViewPoint(viewPoint);
- myRender->drawPoseAxis(devicePose);
- myRender->drawScan(laser == 1 ? laser1Pose : laser2Pose, laser == 1 ? scan1 : scan2, 180. * M_PI / 180., 90. * M_PI / 180.); //draw scan
- myRender->render();
- }
-};
-}
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- std::cout << "\n============================================================\n";
- std::cout << "========== 2D Robot with odometry and 2 LIDARs =============\n";
-
- // USER INPUT ============================================================================================
- if (argc != 2 || atoi(argv[1]) < 1 )
- {
- std::cout << "Please call me with: [./test_ceres_manager NI PRINT], where:" << std::endl;
- std::cout << " - NI is the number of iterations (NI > 0)" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
-
- unsigned int n_execution = (unsigned int) atoi(argv[1]); //number of iterations of the whole execution
-
- // INITIALIZATION ============================================================================================
- //init random generators
- Scalar odom_std_factor = 0.5;
- Scalar gps_std = 1;
- std::default_random_engine generator(1);
- std::normal_distribution<Scalar> distribution_odom(0.0, odom_std_factor); //odometry noise
- std::normal_distribution<Scalar> distribution_gps(0.0, gps_std); //GPS noise
-
- //variables
- Eigen::Vector2s odom_data;
- Eigen::Vector2s gps_fix_reading;
- Eigen::VectorXs ground_truth(n_execution * 3); //all true poses
- Eigen::Vector3s ground_truth_pose; //last true pose
- Eigen::VectorXs odom_trajectory(n_execution * 3); //open loop trajectory
- Eigen::VectorXs mean_times = Eigen::VectorXs::Zero(7);
- clock_t t1, t2;
- Scalar dt = 0.05;
- TimeStamp ts(0);
-
- // Wolf Tree initialization
- Eigen::Vector3s odom_pose = Eigen::Vector3s::Zero();
- Eigen::Vector3s gps_pose = Eigen::Vector3s::Zero();
- Eigen::Vector4s laser_1_pose, laser_2_pose; //xyz + theta
- laser_1_pose << 1.2, 0, 0, 0; //laser 1
- laser_2_pose << -1.2, 0, 0, M_PI; //laser 2
-
- Problem problem(FRM_PO_2D);
- SensorOdom2D* odom_sensor = new SensorOdom2D(std::make_shared<StateBlock>(odom_pose.head(2), true), std::make_shared<StateBlock>(odom_pose.tail(1), true), odom_std_factor, odom_std_factor);
- SensorGPSFix* gps_sensor = new SensorGPSFix(std::make_shared<StateBlock>(gps_pose.head(2), true), std::make_shared<StateBlock>(gps_pose.tail(1), true), gps_std);
- SensorLaser2D* laser_1_sensor = new SensorLaser2D(std::make_shared<StateBlock>(laser_1_pose.head(2), true), std::make_shared<StateBlock>(laser_1_pose.tail(1), true), laserscanutils::LaserScanParams({M_PI/2,-M_PI/2, -M_PI/720,0.01,0.2,100,0.01,0.01}));
- SensorLaser2D* laser_2_sensor = new SensorLaser2D(std::make_shared<StateBlock>(laser_2_pose.head(2), true), std::make_shared<StateBlock>(laser_2_pose.tail(1), true), laserscanutils::LaserScanParams({M_PI/2,-M_PI/2, -M_PI/720,0.01,0.2,100,0.01,0.01}));
- ProcessorTrackerLandmarkCorner* laser_1_processor = new ProcessorTrackerLandmarkCorner(laserscanutils::LineFinderIterativeParams({0.1, 5, 1, 2}), 3, 10);
- ProcessorTrackerLandmarkCorner* laser_2_processor = new ProcessorTrackerLandmarkCorner(laserscanutils::LineFinderIterativeParams({0.1, 5, 1, 2}), 3, 10);
- ProcessorOdom2D* odom_processor = new ProcessorOdom2D(1,1,100);
- odom_sensor->addProcessor(odom_processor);
- laser_1_sensor->addProcessor(laser_1_processor);
- laser_2_sensor->addProcessor(laser_2_processor);
- problem.addSensor(odom_sensor);
- problem.addSensor(gps_sensor);
- problem.addSensor(laser_1_sensor);
- problem.addSensor(laser_2_sensor);
- problem.setProcessorMotion(odom_processor);
-
- CaptureMotion* odom_capture = new CaptureMotion(ts,odom_sensor, odom_data, Eigen::Matrix2s::Identity() * odom_std_factor * odom_std_factor, nullptr);
-
- // Simulated robot
- FaramoticsRobot robot(argc, argv, laser_1_pose, laser_2_pose);
-
- // Initial pose
- ground_truth_pose << 2, 8, 0;
- ground_truth.head(3) = ground_truth_pose;
- odom_trajectory.head(3) = ground_truth_pose;
-
- // Origin Key Frame
- FrameBasePtr origin_frame = problem.createFrame(KEY, ground_truth_pose, ts);
-
- // Prior covariance
- CapturePose* initial_covariance = new CapturePose(ts, gps_sensor, ground_truth_pose, Eigen::Matrix3s::Identity() * 0.1);
- origin_frame->addCapture(initial_covariance);
- initial_covariance->process();
-
- odom_processor->setOrigin(origin_frame);
-
- // Ceres wrapper
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- // ceres_options.minimizer_progress_to_stdout = false;
- // ceres_options.line_search_direction_type = ceres::LBFGS;
- // ceres_options.max_num_iterations = 100;
- google::InitGoogleLogging(argv[0]);
-
- CeresManager ceres_manager(&problem, ceres_options);
- std::ofstream log_file, landmark_file; //output file
-
- //std::cout << "START TRAJECTORY..." << std::endl;
- // START TRAJECTORY ============================================================================================
- for (unsigned int step = 1; step < n_execution; step++)
- {
- // timestamp
- ts = TimeStamp(step*dt);
-
- //get init time
- t2 = clock();
-
- // ROBOT MOVEMENT ---------------------------
- //std::cout << "ROBOT MOVEMENT..." << std::endl;
- // moves the device position
- t1 = clock();
- ground_truth_pose = robot.motionCampus(step, odom_data(0), odom_data(1));
- ground_truth.segment(step * 3, 3) = ground_truth_pose;
-
- // ODOMETRY DATA -------------------------------------
- // noisy odometry
- odom_data(0) += distribution_odom(generator) * (odom_data(0) == 0 ? 1e-6 : odom_data(0));
- odom_data(1) += distribution_odom(generator) * (odom_data(1) == 0 ? 1e-6 : odom_data(1));
- // process odometry
- odom_capture->setTimeStamp(TimeStamp(ts));
- odom_capture->setData(odom_data);
- odom_processor->process(odom_capture);
- // odometry integration
- odom_trajectory.segment(step * 3, 3) = problem.getCurrentState();
-
- // LIDAR DATA ---------------------------
- if (step % 3 == 0)
- {
- std::cout << "--PROCESS LIDAR 1 DATA..." << laser_1_sensor->id() << std::endl;
- laser_1_processor->process(new CaptureLaser2D(ts, laser_1_sensor, robot.computeScan(1)));
- std::cout << "--PROCESS LIDAR 2 DATA..." << laser_2_sensor->id() << std::endl;
- laser_2_processor->process(new CaptureLaser2D(ts, laser_2_sensor, robot.computeScan(2)));
- }
-
- // GPS DATA ---------------------------
- if (step % 5 == 0)
- {
- // compute GPS
- gps_fix_reading = ground_truth_pose.head<2>();
- gps_fix_reading(0) += distribution_gps(generator);
- gps_fix_reading(1) += distribution_gps(generator);
- // process data
- //(new CaptureGPSFix(ts, &gps_sensor, gps_fix_reading, gps_std * Eigen::MatrixXs::Identity(3,3)));
- }
- mean_times(0) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // SOLVE OPTIMIZATION ---------------------------
- //std::cout << "SOLVING..." << std::endl;
- t1 = clock();
- ceres::Solver::Summary summary = ceres_manager.solve();
- //std::cout << summary.FullReport() << std::endl;
- mean_times(3) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // COMPUTE COVARIANCES ---------------------------
- //std::cout << "COMPUTING COVARIANCES..." << std::endl;
- t1 = clock();
- ceres_manager.computeCovariances();
- mean_times(4) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // DRAWING STUFF ---------------------------
- //std::cout << "RENDERING..." << std::endl;
- t1 = clock();
- if (step % 3 == 0)
- robot.render(laser_1_processor->getLast() == nullptr ? FeatureBasePtrList({}) : *laser_1_processor->getLast()->getFeatureList(), 1, *problem.getMap()->getLandmarkList(), problem.getCurrentState());
- //robot.render(laser_2_processor->getLast() == nullptr ? FeatureBasePtrList({}) : *laser_2_processor->getLast()->getFeatureList(), 2, *problem.getMap()->getLandmarkList(), problem.getCurrentState());
- mean_times(5) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // TIME MANAGEMENT ---------------------------
- double total_t = ((double) clock() - t2) / CLOCKS_PER_SEC;
- mean_times(6) += total_t;
- if (total_t < 0.5)
- usleep(500000 - 1e6 * total_t);
-
-// std::cout << "\nTree after step..." << std::endl;
- }
-
- // DISPLAY RESULTS ============================================================================================
- mean_times /= n_execution;
- std::cout << "\nSIMULATION AVERAGE LOOP DURATION [s]" << std::endl;
- std::cout << " data generation: " << mean_times(0) << std::endl;
- std::cout << " wolf managing: " << mean_times(1) << std::endl;
- std::cout << " ceres managing: " << mean_times(2) << std::endl;
- std::cout << " ceres optimization: " << mean_times(3) << std::endl;
- std::cout << " ceres covariance: " << mean_times(4) << std::endl;
- std::cout << " results drawing: " << mean_times(5) << std::endl;
- std::cout << " loop time: " << mean_times(6) << std::endl;
-
- // std::cout << "\nTree before deleting..." << std::endl;
-
- // Draw Final result -------------------------
- robot.render(laser_1_processor->getLast() == nullptr ? FeatureBasePtrList({}) : *laser_1_processor->getLast()->getFeatureList(), 1, *problem.getMap()->getLandmarkList(), problem.getCurrentState());
-
- // Print Final result in a file -------------------------
- // Vehicle poses
- int i = 0;
- Eigen::VectorXs state_poses = Eigen::VectorXs::Zero(n_execution * 3);
- for (auto frame : *(problem.getTrajectory()->getFrameList()))
- {
- state_poses.segment(i, 3) << frame->getP()->getVector(), frame->getO()->getVector();
- i += 3;
- }
-
- // Landmarks
- i = 0;
- Eigen::VectorXs landmarks = Eigen::VectorXs::Zero(problem.getMap()->getLandmarkList()->size() * 2);
- for (auto landmark : *(problem.getMap()->getLandmarkList()))
- {
- landmarks.segment(i, 2) = landmark->getP()->getVector();
- i += 2;
- }
-
- // Print log files
- std::string filepath = getenv("HOME") + std::string("/Desktop/log_file_2.txt");
- log_file.open(filepath, std::ofstream::out); //open log file
-
- if (log_file.is_open())
- {
- log_file << 0 << std::endl;
- for (unsigned int ii = 0; ii < n_execution; ii++)
- log_file << state_poses.segment(ii * 3, 3).transpose() << "\t" << ground_truth.segment(ii * 3, 3).transpose() << "\t" << (state_poses.segment(ii * 3, 3) - ground_truth.segment(ii * 3, 3)).transpose() << "\t" << odom_trajectory.segment(ii * 3, 3).transpose() << std::endl;
- log_file.close(); //close log file
- std::cout << std::endl << "Result file " << filepath << std::endl;
- }
- else
- std::cout << std::endl << "Failed to write the log file " << filepath << std::endl;
-
- std::string filepath2 = getenv("HOME") + std::string("/Desktop/landmarks_file_2.txt");
- landmark_file.open(filepath2, std::ofstream::out); //open log file
-
- if (landmark_file.is_open())
- {
- for (unsigned int ii = 0; ii < landmarks.size(); ii += 2)
- landmark_file << landmarks.segment(ii, 2).transpose() << std::endl;
- landmark_file.close(); //close log file
- std::cout << std::endl << "Landmark file " << filepath << std::endl;
- }
- else
- std::cout << std::endl << "Failed to write the landmark file " << filepath << std::endl;
-
- std::cout << "Press any key for ending... " << std::endl << std::endl;
- std::getchar();
-
- std::cout << " ========= END ===========" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_ceres_2_lasers_polylines.cpp b/demos/demo_ceres_2_lasers_polylines.cpp
deleted file mode 100644
index 62ad277f9..000000000
--- a/demos/demo_ceres_2_lasers_polylines.cpp
+++ /dev/null
@@ -1,377 +0,0 @@
-//std includes
-#include "base/sensor/sensor_GPS_fix.h"
-#include <cstdlib>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// Eigen includes
-#include <eigen3/Eigen/Dense>
-#include <eigen3/Eigen/Geometry>
-
-//Ceres includes
-#include "glog/logging.h"
-
-//Wolf includes
-#include "base/problem/problem.h"
-#include "base/processor/processor_tracker_landmark_polyline.h"
-#include "base/processor/processor_odom_2D.h"
-#include "base/sensor/sensor_laser_2D.h"
-#include "base/sensor/sensor_odom_2D.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-
-// laserscanutils
-#include "laser_scan_utils/line_finder_iterative.h"
-#include "laser_scan_utils/laser_scan.h"
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-#include "base/capture/capture_pose.h"
-//faramotics includes
-#include "faramotics/dynamicSceneRender.h"
-#include "faramotics/rangeScan2D.h"
-#include "btr-headers/pose3d.h"
-
-namespace wolf {
-class FaramoticsRobot
-{
- public:
-
- Cpose3d viewPoint, devicePose, laser1Pose, laser2Pose, estimated_vehicle_pose, estimated_laser_1_pose, estimated_laser_2_pose;
- vector < Cpose3d > devicePoses;
- vector<float> scan1, scan2;
- string modelFileName;
- CrangeScan2D* myScanner;
- CdynamicSceneRender* myRender;
- Eigen::Vector3s ground_truth_pose_;
- Eigen::Vector4s laser_1_pose_, laser_2_pose_;
-
- FaramoticsRobot(int argc, char** argv, const Eigen::Vector4s& _laser_1_pose, const Eigen::Vector4s& _laser_2_pose) :
- modelFileName("/home/jvallve/iri-lab/faramotics/models/campusNordUPC.obj"),
- laser_1_pose_(_laser_1_pose),
- laser_2_pose_(_laser_2_pose)
- {
- devicePose.setPose(2, 8, 0.2, 0, 0, 0);
- viewPoint.setPose(devicePose);
- viewPoint.moveForward(10);
- viewPoint.rt.setEuler(viewPoint.rt.head() + M_PI / 2, viewPoint.rt.pitch() + 30. * M_PI / 180., viewPoint.rt.roll());
- viewPoint.moveForward(-15);
- //glut initialization
- faramotics::initGLUT(argc, argv);
- //create a viewer for the 3D model and scan points
- myRender = new CdynamicSceneRender(1200, 700, 90 * M_PI / 180, 90 * 700.0 * M_PI / (1200.0 * 180.0), 0.2, 100);
- myRender->loadAssimpModel(modelFileName, true); //with wireframe
- //create scanner and load 3D model
- myScanner = new CrangeScan2D(HOKUYO_UTM30LX_180DEG); //HOKUYO_UTM30LX_180DEG or LEUZE_RS4
- myScanner->loadAssimpModel(modelFileName);
- }
-
- //function travel around
- Eigen::Vector3s motionCampus(unsigned int ii, double& displacement_, double& rotation_)
- {
- if (ii <= 120){ displacement_ = 0.1; rotation_ = 0; }
- else if (ii <= 170) { displacement_ = 0.2; rotation_ = 1.8 * M_PI / 180; }
- else if (ii <= 220) { displacement_ = 0; rotation_ =-1.8 * M_PI / 180; }
- else if (ii <= 310) { displacement_ = 0.1; rotation_ = 0; }
- else if (ii <= 487) { displacement_ = 0.1; rotation_ =-1.0 * M_PI / 180; }
- else if (ii <= 600) { displacement_ = 0.2; rotation_ = 0; }
- else if (ii <= 700) { displacement_ = 0.1; rotation_ =-1.0 * M_PI / 180; }
- else if (ii <= 780) { displacement_ = 0; rotation_ =-1.0 * M_PI / 180; }
- else { displacement_ = 0.3; rotation_ = 0; }
-
- devicePose.moveForward(displacement_);
- devicePose.rt.setEuler(devicePose.rt.head() + rotation_, devicePose.rt.pitch(), devicePose.rt.roll());
-
- // laser 1
- laser1Pose.setPose(devicePose);
- laser1Pose.moveForward(laser_1_pose_(0));
- // laser 2
- laser2Pose.setPose(devicePose);
- laser2Pose.moveForward(laser_2_pose_(0));
- laser2Pose.rt.setEuler(laser2Pose.rt.head() + laser_2_pose_(3), laser2Pose.rt.pitch(), laser2Pose.rt.roll());
-
- devicePoses.push_back(devicePose);
-
- ground_truth_pose_ << devicePose.pt(0), devicePose.pt(1), devicePose.rt.head();
- return ground_truth_pose_;
- }
-
- ~FaramoticsRobot()
- {
- std::cout << "deleting render and scanner.." << std::endl;
- delete myRender;
- delete myScanner;
- std::cout << "deleted!" << std::endl;
- }
-
- //compute scans
- vector<float> computeScan(const int scan_id)
- {
- if (scan_id == 1)
- {
- scan1.clear();
- myScanner->computeScan(laser1Pose, scan1);
- return scan1;
- }
- else
- {
- scan2.clear();
- myScanner->computeScan(laser2Pose, scan2);
- return scan2;
- }
- }
-
- void render(const FeatureBasePtrList& feature_list, int laser, const LandmarkBasePtrList& landmark_list, const Eigen::Vector3s& estimated_pose)
- {
- // detected corners
- std::cout << " drawCorners: " << feature_list.size() << std::endl;
- std::vector<double> corner_vector;
- corner_vector.reserve(2*feature_list.size());
- for (auto corner : feature_list)
- {
- std::cout << " corner " << corner->id() << std::endl;
- corner_vector.push_back(corner->getMeasurement(0));
- corner_vector.push_back(corner->getMeasurement(1));
- }
- myRender->drawCorners(laser == 1 ? laser1Pose : laser2Pose, corner_vector);
-
- // landmarks
- std::cout << " drawLandmarks: " << landmark_list.size() << std::endl;
- std::vector<double> landmark_vector;
- landmark_vector.reserve(3*landmark_list.size());
- for (auto landmark : landmark_list)
- {
- Scalar* position_ptr = landmark->getP()->get();
- landmark_vector.push_back(*position_ptr); //x
- landmark_vector.push_back(*(position_ptr + 1)); //y
- landmark_vector.push_back(0.2); //z
- }
- myRender->drawLandmarks(landmark_vector);
-
- // draw localization and sensors
- estimated_vehicle_pose.setPose(estimated_pose(0), estimated_pose(1), 0.2, estimated_pose(2), 0, 0);
- estimated_laser_1_pose.setPose(estimated_vehicle_pose);
- estimated_laser_1_pose.moveForward(laser_1_pose_(0));
- estimated_laser_2_pose.setPose(estimated_vehicle_pose);
- estimated_laser_2_pose.moveForward(laser_2_pose_(0));
- estimated_laser_2_pose.rt.setEuler(estimated_laser_2_pose.rt.head() + laser_2_pose_(3), estimated_laser_2_pose.rt.pitch(), estimated_laser_2_pose.rt.roll());
- myRender->drawPoseAxisVector( { estimated_vehicle_pose, estimated_laser_1_pose, estimated_laser_2_pose });
-
- //Set view point and render the scene
- //locate visualization view point, somewhere behind the device
- // viewPoint.setPose(devicePose);
- // viewPoint.rt.setEuler( viewPoint.rt.head(), viewPoint.rt.pitch()+20.*M_PI/180., viewPoint.rt.roll() );
- // viewPoint.moveForward(-5);
- myRender->setViewPoint(viewPoint);
- myRender->drawPoseAxis(devicePose);
- myRender->drawScan(laser == 1 ? laser1Pose : laser2Pose, laser == 1 ? scan1 : scan2, 180. * M_PI / 180., 90. * M_PI / 180.); //draw scan
- myRender->render();
- }
-};
-}
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- std::cout << "\n============================================================\n";
- std::cout << "========== 2D Robot with odometry and 2 LIDARs =============\n";
-
- // USER INPUT ============================================================================================
- if (argc != 2 || atoi(argv[1]) < 1 )
- {
- std::cout << "Please call me with: [./test_ceres_manager NI PRINT], where:" << std::endl;
- std::cout << " - NI is the number of iterations (NI > 0)" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
-
- unsigned int n_execution = (unsigned int) atoi(argv[1]); //number of iterations of the whole execution
-
- // INITIALIZATION ============================================================================================
- //init random generators
- Scalar odom_std_factor = 0.5;
- Scalar gps_std = 1;
- std::default_random_engine generator(1);
- std::normal_distribution<Scalar> distribution_odom(0.0, odom_std_factor); //odometry noise
- std::normal_distribution<Scalar> distribution_gps(0.0, gps_std); //GPS noise
-
- //variables
- Eigen::Vector2s odom_data;
- Eigen::Vector2s gps_fix_reading;
- Eigen::VectorXs ground_truth(n_execution * 3); //all true poses
- Eigen::Vector3s ground_truth_pose; //last true pose
- Eigen::VectorXs odom_trajectory(n_execution * 3); //open loop trajectory
- Eigen::VectorXs mean_times = Eigen::VectorXs::Zero(7);
- clock_t t1, t2;
- Scalar dt = 0.05;
- TimeStamp ts(0);
-
- // Wolf Tree initialization
- Eigen::Vector3s odom_pose = Eigen::Vector3s::Zero();
- Eigen::Vector3s gps_pose = Eigen::Vector3s::Zero();
- Eigen::Vector4s laser_1_pose, laser_2_pose; //xyz + theta
- laser_1_pose << 1.2, 0, 0, 0; //laser 1
- laser_2_pose << -1.2, 0, 0, M_PI; //laser 2
-
- Problem problem(FRM_PO_2D);
- SensorOdom2D* odom_sensor = new SensorOdom2D(std::make_shared<StateBlock>(odom_pose.head(2), true), std::make_shared<StateBlock>(odom_pose.tail(1), true), odom_std_factor, odom_std_factor);
- SensorGPSFix* gps_sensor = new SensorGPSFix(std::make_shared<StateBlock>(gps_pose.head(2), true), std::make_shared<StateBlock>(gps_pose.tail(1), true), gps_std);
- SensorLaser2D* laser_1_sensor = new SensorLaser2D(std::make_shared<StateBlock>(laser_1_pose.head(2), true), std::make_shared<StateBlock>(laser_1_pose.tail(1), true), laserscanutils::LaserScanParams({M_PI/2,-M_PI/2, -M_PI/720,0.01,0.2,100,0.01,0.01}));
- SensorLaser2D* laser_2_sensor = new SensorLaser2D(std::make_shared<StateBlock>(laser_2_pose.head(2), true), std::make_shared<StateBlock>(laser_2_pose.tail(1), true), laserscanutils::LaserScanParams({M_PI/2,-M_PI/2, -M_PI/720,0.01,0.2,100,0.01,0.01}));
-
- wolf::ProcessorParamsPolyline laser_processor_params;
- laser_processor_params.line_finder_params = laserscanutils::LineFinderIterativeParams({0.1, 5, 1, 2});
- laser_processor_params.new_features_th = 3;
- laser_processor_params.loop_frames_th = 10;
- laser_processor_params.time_tolerance = 0.1;
- laser_processor_params.position_error_th = 0.5;
- ProcessorTrackerLandmarkPolyline* laser_1_processor = new ProcessorTrackerLandmarkPolyline(laser_processor_params);
- ProcessorTrackerLandmarkPolyline* laser_2_processor = new ProcessorTrackerLandmarkPolyline(laser_processor_params);
- ProcessorOdom2D* odom_processor = new ProcessorOdom2D(1,1,100);
- odom_sensor->addProcessor(odom_processor);
- laser_1_sensor->addProcessor(laser_1_processor);
- laser_2_sensor->addProcessor(laser_2_processor);
- problem.addSensor(odom_sensor);
- problem.addSensor(gps_sensor);
- problem.addSensor(laser_1_sensor);
- problem.addSensor(laser_2_sensor);
- problem.setProcessorMotion(odom_processor);
-
- CaptureMotion* odom_capture = new CaptureMotion(ts,odom_sensor, odom_data, Eigen::Matrix2s::Identity() * odom_std_factor * odom_std_factor, nullptr);
-
- // Simulated robot
- FaramoticsRobot robot(argc, argv, laser_1_pose, laser_2_pose);
-
- // Initial pose
- ground_truth_pose << 2, 8, 0;
- ground_truth.head(3) = ground_truth_pose;
- odom_trajectory.head(3) = ground_truth_pose;
-
- // Origin Key Frame
- FrameBasePtr origin_frame = problem.createFrame(KEY, ground_truth_pose, ts);
-
- // Prior covariance
- CapturePose* initial_covariance = new CapturePose(ts, gps_sensor, ground_truth_pose, Eigen::Matrix3s::Identity() * 0.1);
- origin_frame->addCapture(initial_covariance);
- initial_covariance->process();
-
- odom_processor->setOrigin(origin_frame);
-
- // Ceres wrapper
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- // ceres_options.minimizer_progress_to_stdout = false;
- // ceres_options.line_search_direction_type = ceres::LBFGS;
- // ceres_options.max_num_iterations = 100;
- google::InitGoogleLogging(argv[0]);
-
- CeresManager ceres_manager(&problem, ceres_options);
- std::ofstream log_file, landmark_file; //output file
-
- //std::cout << "START TRAJECTORY..." << std::endl;
- // START TRAJECTORY ============================================================================================
- for (unsigned int step = 1; step < n_execution; step++)
- {
- // timestamp
- ts = TimeStamp(step*dt);
-
- //get init time
- t2 = clock();
-
- // ROBOT MOVEMENT ---------------------------
- //std::cout << "ROBOT MOVEMENT..." << std::endl;
- // moves the device position
- t1 = clock();
- ground_truth_pose = robot.motionCampus(step, odom_data(0), odom_data(1));
- ground_truth.segment(step * 3, 3) = ground_truth_pose;
-
- // ODOMETRY DATA -------------------------------------
- // noisy odometry
- odom_data(0) += distribution_odom(generator) * (odom_data(0) == 0 ? 1e-6 : odom_data(0));
- odom_data(1) += distribution_odom(generator) * (odom_data(1) == 0 ? 1e-6 : odom_data(1));
- // process odometry
- odom_capture->setTimeStamp(TimeStamp(ts));
- odom_capture->setData(odom_data);
- odom_processor->process(odom_capture);
- // odometry integration
- odom_trajectory.segment(step * 3, 3) = problem.getCurrentState();
-
- // LIDAR DATA ---------------------------
- if (step % 3 == 0)
- {
- std::cout << "--PROCESS LIDAR 1 DATA..." << laser_1_sensor->id() << std::endl;
- laser_1_processor->process(new CaptureLaser2D(ts, laser_1_sensor, robot.computeScan(1)));
- std::cout << "--PROCESS LIDAR 2 DATA..." << laser_2_sensor->id() << std::endl;
- laser_2_processor->process(new CaptureLaser2D(ts, laser_2_sensor, robot.computeScan(2)));
- }
-
- // GPS DATA ---------------------------
- if (step % 5 == 0)
- {
- // compute GPS
- gps_fix_reading = ground_truth_pose.head<2>();
- gps_fix_reading(0) += distribution_gps(generator);
- gps_fix_reading(1) += distribution_gps(generator);
- // process data
- //(new CaptureGPSFix(ts, &gps_sensor, gps_fix_reading, gps_std * Eigen::MatrixXs::Identity(3,3)));
- }
- mean_times(0) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // SOLVE OPTIMIZATION ---------------------------
- std::cout << "SOLVING..." << std::endl;
- t1 = clock();
- std::string summary = ceres_manager.solve(2);// 0: nothing, 1: BriefReport, 2: FullReport
- std::cout << summary << std::endl;
- mean_times(3) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // COMPUTE COVARIANCES ---------------------------
- std::cout << "COMPUTING COVARIANCES..." << std::endl;
- t1 = clock();
- //ceres_manager.computeCovariances();
- mean_times(4) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // DRAWING STUFF ---------------------------
- std::cout << "RENDERING..." << std::endl;
- t1 = clock();
-// if (step % 3 == 0)
-// robot.render(laser_1_processor->getLast() == nullptr ? FeatureBasePtrList({}) : *laser_1_processor->getLast()->getFeatureList(), 1, *problem.getMap()->getLandmarkList(), problem.getCurrentState());
- //robot.render(laser_2_processor->getLast() == nullptr ? FeatureBasePtrList({}) : *laser_2_processor->getLast()->getFeatureList(), 2, *problem.getMap()->getLandmarkList(), problem.getCurrentState());
- mean_times(5) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // TIME MANAGEMENT ---------------------------
- double total_t = ((double) clock() - t2) / CLOCKS_PER_SEC;
- mean_times(6) += total_t;
- if (total_t < 0.5)
- usleep(500000 - 1e6 * total_t);
-
-// std::cout << "\nTree after step..." << std::endl;
- }
-
- // DISPLAY RESULTS ============================================================================================
- mean_times /= n_execution;
- std::cout << "\nSIMULATION AVERAGE LOOP DURATION [s]" << std::endl;
- std::cout << " data generation: " << mean_times(0) << std::endl;
- std::cout << " wolf managing: " << mean_times(1) << std::endl;
- std::cout << " ceres managing: " << mean_times(2) << std::endl;
- std::cout << " ceres optimization: " << mean_times(3) << std::endl;
- std::cout << " ceres covariance: " << mean_times(4) << std::endl;
- std::cout << " results drawing: " << mean_times(5) << std::endl;
- std::cout << " loop time: " << mean_times(6) << std::endl;
-
- std::cout << "\nTree before deleting..." << std::endl;
-
- std::cout << "Press any key for ending... " << std::endl << std::endl;
- std::getchar();
-
- std::cout << " ========= END ===========" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_diff_drive.cpp b/demos/demo_diff_drive.cpp
deleted file mode 100644
index 561cb2676..000000000
--- a/demos/demo_diff_drive.cpp
+++ /dev/null
@@ -1,297 +0,0 @@
-/**
- * \file test_diff_drive.cpp
- *
- * Created on: Oct 26, 2017
- * \author: Jeremie Deray
- */
-
-//Wolf
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/sensor/sensor_diff_drive.h"
-#include "base/capture/capture_wheel_joint_position.h"
-#include "base/processor/processor_diff_drive.h"
-
-//std
-#include <iostream>
-#include <fstream>
-#include <iomanip>
-#include <ctime>
-#include <cmath>
-
-//#define DEBUG_RESULTS
-
-void getOdom2DData(std::ifstream& _stream, wolf::Scalar& _stamp, Eigen::Vector2s& _data)
-{
- /*
- * Data are logged as follows :
- *
- * header:
- * seq: xxx
- * stamp:
- * secs: xxx
- * nsecs: xxx
- * frame_id: ''
- * twist:
- * linear:
- * x: 0.0
- * y: 0.0
- * z: 0.0
- * angular:
- * x: 0.0
- * y: 0.0
- * z: 0.0
- * ---
- */
-
- std::string dummy;
-
- getline(_stream, dummy); // header:
- getline(_stream, dummy); // seq: xxx
- getline(_stream, dummy); // stamp:
- getline(_stream, dummy); // secs: xxx
-
- // Find secs
- std::string sub("secs: ");
- std::string::size_type i = dummy.find(sub);
- dummy.erase(i, sub.length());
-
- _stamp = std::stod(dummy);
-
- // Find nsecs
- getline(_stream, dummy); // nsecs: xxx
- sub = "nsecs: ";
- i = dummy.find(sub);
- dummy.erase(i, sub.length());
-
- _stamp += std::stod(dummy) * wolf::Scalar(1e-9);
-
- getline(_stream, dummy); // frame_id: ''
- getline(_stream, dummy); // twist:
- getline(_stream, dummy); // linear:
- getline(_stream, dummy); // x: 0.0
-
- sub = "x: ";
- i = dummy.find(sub);
- dummy.erase(i, sub.length());
-
- _data(0) = std::stod(dummy);
-
- getline(_stream, dummy); // y: 0.0
- getline(_stream, dummy); // z: 0.0
- getline(_stream, dummy); // angular:
- getline(_stream, dummy); // x: 0.0
- getline(_stream, dummy); // y: 0.0
- getline(_stream, dummy); // z: 0.0
-
- sub = "z: ";
- i = dummy.find(sub);
- dummy.erase(i, sub.length());
-
- _data(1) = std::stod(dummy);
-
- getline(_stream, dummy); // ---
-}
-
-void readWheelData(std::ifstream &_stream, Eigen::Vector2s &_data)
-{
- /*
- * left_wheel_joint_actual_position: [x]
- * right_wheel_joint_actual_position: [x]
- * ---
- */
-
- std::string dummy;
- std::string l_brac("[");
- std::string r_brac("]");
-
- getline(_stream, dummy);
-
- unsigned first = dummy.find(l_brac);
- unsigned last = dummy.find(r_brac);
-
- //std::cout << "READING : " << dummy.substr(first+1, last-first-1) << std::endl;
-
- _data(0) = std::stod(dummy.substr(first+1, last-first-1));
-
- getline(_stream, dummy);
-
- first = dummy.find(l_brac);
- last = dummy.find(r_brac);
-
- //std::cout << "READING : " << dummy.substr(first+1, last-first-1) << std::endl;
-
- _data(1) = std::stod(dummy.substr(first+1 , last-first-1));
-
- getline(_stream, dummy);
-}
-
-bool WHEEL_DATA = true;
-bool VERBOSE = false;
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- WOLF_INFO("==================== diff drive test ======================");
-
- //load files containing data
- std::ifstream data_file;
- const char * filename;
-
- if (argc < 2)
- {
- WOLF_ERROR("Missing input argument! :"
- " needs 2 arguments (path to data file & data type "
- "- velocities or wheel positions).");
- return EXIT_FAILURE;
- }
- else
- {
- filename = argv[1];
- if (argc >= 3) WHEEL_DATA = std::stoi(argv[2]);
-
- data_file.open(filename);
-
- WOLF_INFO("Data file: ", filename);
-
- if (!data_file.is_open())
- {
- WOLF_ERROR("Failed to open data files... Exiting");
- return EXIT_FAILURE;
- }
- }
-
- // Wolf problem
- ProblemPtr wolf_problem_ptr_ = Problem::create("PO", 2);
-
- const std::string sensor_name("Main Odometer");
- Eigen::VectorXs extrinsics(3);
- extrinsics << 0, 0, 0;
-
- IntrinsicsBasePtr intrinsics = std::make_shared<IntrinsicsDiffDrive>();
-
- IntrinsicsDiffDrivePtr intrinsics_diff_drive =
- std::static_pointer_cast<IntrinsicsDiffDrive>(intrinsics);
-
- intrinsics_diff_drive->left_radius_ = 0.1;
- intrinsics_diff_drive->right_radius_ = 0.1;
- intrinsics_diff_drive->separation_ = 0.3517;
-
- intrinsics_diff_drive->model_ = wolf::DiffDriveModel::Three_Factor_Model;
- intrinsics_diff_drive->factors_ = Eigen::Vector3s(1,1,1);
-
- intrinsics_diff_drive->left_resolution_ = 0.0001653; // [rad]
- intrinsics_diff_drive->right_resolution_ = 0.0001653; // [rad]
-
- intrinsics_diff_drive->left_gain_ = 0.01;
- intrinsics_diff_drive->right_gain_ = 0.01;
-
- // Time and data variables
- TimeStamp t;
- Scalar stamp_secs(0);
-// Scalar period_secs(0.010); //100Hz
- Scalar period_secs(0.020); //50Hz
- Eigen::Vector2s data_; data_ << 0,0;
-
- const auto scalar_max = std::numeric_limits<Scalar>::max();
-
- ProcessorParamsDiffDrivePtr processor_params = std::make_shared<ProcessorParamsDiffDrive>();
- processor_params->time_tolerance = period_secs/2;
- processor_params->angle_turned = scalar_max;
- processor_params->dist_traveled = scalar_max;
- processor_params->max_time_span = scalar_max;
- processor_params->max_buff_length = 999;
- processor_params->unmeasured_perturbation_std = 0.0001;
-
- SensorBasePtr sensor_ptr =
- wolf_problem_ptr_->installSensor("DIFF DRIVE", sensor_name, extrinsics, intrinsics);
-
- WOLF_INFO("Sensor 'DIFF DRIVE' installed.");
-
- auto diff_drive_sensor_ptr = std::static_pointer_cast<SensorDiffDrive>(sensor_ptr);
-
- wolf_problem_ptr_->installProcessor("DIFF DRIVE", "Diffential Drive processor", sensor_ptr, processor_params);
-
- WOLF_INFO("Processor 'DIFF DRIVE' installed.");
-
- // Get initial wheel data
- if (WHEEL_DATA)
- readWheelData(data_file, data_);
- else
- getOdom2DData(data_file, stamp_secs, data_);
-
- t.set(stamp_secs);
- auto processor_diff_drive_ptr =
- std::static_pointer_cast<ProcessorDiffDrive>(wolf_problem_ptr_->getProcessorMotion());
- processor_diff_drive_ptr->setTimeTolerance(period_secs/2); // overwrite time tolerance based on new evidence
-
- // Set the origin
- // Create one capture to store the Odometry data.
- std::shared_ptr<CaptureWheelJointPosition> data_ptr =
- std::make_shared<CaptureWheelJointPosition>(t, sensor_ptr, data_, nullptr);
-
- WOLF_INFO("Process first capture.");
-
- diff_drive_sensor_ptr->process(data_ptr);
-
- // main loop
- clock_t begin = clock();
-
- while (!data_file.eof())
- {
- // read new data
- if (WHEEL_DATA)
- {
- readWheelData(data_file, data_);
- stamp_secs += period_secs;
- }
- else
- getOdom2DData(data_file, stamp_secs, data_);
-
- t.set(stamp_secs);
-
- data_ptr = std::make_shared<CaptureWheelJointPosition>(t, sensor_ptr, data_, nullptr);
-
- // process data in capture
- diff_drive_sensor_ptr->process(data_ptr);
-
- WOLF_INFO_COND(VERBOSE, "At stamp ", stamp_secs,
- " state ", processor_diff_drive_ptr->getCurrentState().transpose());
- }
-
- data_file.close();
-
- double elapsed_secs = double(clock() - begin) / CLOCKS_PER_SEC;
-
- // Final state
- WOLF_INFO("----------------------------------------- "
- "Integration results "
- "-----------------------------------------");
-
- WOLF_INFO("Integrated delta: " , /* std::fixed , std::setprecision(3),*/
- wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_.transpose());
- WOLF_INFO("Integrated state: " , /*std::fixed , std::setprecision(3),*/
- wolf_problem_ptr_->getProcessorMotion()->getCurrentState().transpose());
- WOLF_INFO("Integrated std : " , /*std::fixed , std::setprecision(3),*/
- (wolf_problem_ptr_->getProcessorMotion()->getMotion().
- delta_integr_cov_.diagonal().transpose()).array().sqrt());
-
- // Print statistics
- TimeStamp t0, tf;
- t0 = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().front().ts_;
- tf = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
-
- double N = (double)wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().size();
-
- WOLF_INFO("t0 : " , t0.get() , " secs");
- WOLF_INFO("tf : " , tf.get() , " secs");
- WOLF_INFO("duration : " , tf-t0 , " secs");
- WOLF_INFO("N samples : " , N );
- WOLF_INFO("frequency : " , (N-1)/(tf-t0) , " Hz" );
- WOLF_INFO("CPU time : " , elapsed_secs , " s" );
- WOLF_INFO("s/integr : " , elapsed_secs/(N-1)*1e6 , " us" );
- WOLF_INFO("integr/s : " , (N-1)/elapsed_secs , " ips" );
-
- return 0;
-}
diff --git a/demos/demo_eigen_quaternion.cpp b/demos/demo_eigen_quaternion.cpp
deleted file mode 100644
index d24a715cb..000000000
--- a/demos/demo_eigen_quaternion.cpp
+++ /dev/null
@@ -1,34 +0,0 @@
-
-//std
-#include <iostream>
-
-//Eigen
-#include <eigen3/Eigen/Geometry>
-
-//Wolf
-#include "base/common/wolf.h"
-
-int main()
-{
- using namespace wolf;
-
- std::cout << std::endl << "Eigen Quatenrnion test" << std::endl;
-
- Scalar q1[4];
- Eigen::Map<Eigen::Quaternions> q1_map(q1);
-
- //try to find out how eigen sorts storage (real part tail or head ? )
- q1_map.w() = 1;
- q1_map.x() = 2;
- q1_map.y() = 3;
- q1_map.z() = 4;
- std::cout << "q1[0]=" << q1[0] << "; q1_map.x()=" << q1_map.x() << std::endl;
- std::cout << "q1[1]=" << q1[1] << "; q1_map.y()=" << q1_map.y() << std::endl;
- std::cout << "q1[2]=" << q1[2] << "; q1_map.z()=" << q1_map.z() << std::endl;
- std::cout << "q1[3]=" << q1[3] << "; q1_map.w()=" << q1_map.w() << std::endl;
- std::cout << std::endl << "RESULT: Eigen stores REAL part in the LAST memory position of the quaternion." << std::endl;
-
- std::cout << std::endl << "End of Eigen Quatenrnion test" << std::endl;
- return 0;
-}
-
diff --git a/demos/demo_eigen_template.cpp b/demos/demo_eigen_template.cpp
deleted file mode 100644
index 47e5aa419..000000000
--- a/demos/demo_eigen_template.cpp
+++ /dev/null
@@ -1,105 +0,0 @@
-/**
- * \file test_eigen_template.cpp
- *
- * Created on: Sep 12, 2016
- * \author: jsola
- */
-
-#include <eigen3/Eigen/Dense>
-#include <eigen3/Eigen/Geometry>
-#include <iostream>
-
-template <int Size, int DesiredSize>
-struct StaticSizeCheck {
- template <typename T>
- StaticSizeCheck(const T&) {
- static_assert(Size == DesiredSize, "Static sizes do not match");
- }
-};
-
-template <int DesiredSize>
-struct StaticSizeCheck<Eigen::Dynamic, DesiredSize> {
- template <typename T>
- StaticSizeCheck(const T& t) {
- assert(t == DesiredSize && "Dynamic sizes do not match");
- }
-};
-
-template <int DesiredR, int DesiredC>
-struct MatrixSizeCheck {
- template <typename T>
- static void check(const T& t) {
- StaticSizeCheck<T::RowsAtCompileTime, DesiredR>(t.rows());
- StaticSizeCheck<T::ColsAtCompileTime, DesiredC>(t.cols());
- }
-};
-
-template<typename Derived>
-inline Eigen::Quaternion<typename Derived::Scalar> v2q(const Eigen::MatrixBase<Derived>& _v){
-
- MatrixSizeCheck<3, 1>::check(_v);
-
- Eigen::Quaternion<typename Derived::Scalar> q;
- typename Derived::Scalar angle = _v.norm();
- typename Derived::Scalar angle_half = angle/2.0;
- if (angle > 1e-8)
- {
- q.w() = cos(angle_half);
- q.vec() = _v / angle * sin(angle_half);
- return q;
- }
- else
- {
- q.w() = cos(angle_half);
- q.vec() = _v * ( (typename Derived::Scalar)0.5 - angle_half*angle_half/(typename Derived::Scalar)12.0 ); // see the Taylor series of sinc(x) ~ 1 - x^2/3!, and have q.vec = v/2 * sinc(angle_half)
- return q;
- }
-}
-
-int main(void)
-{
- using namespace Eigen;
-
- VectorXd x(10);
- x << 1,2,3,4,5,6,7,8,9,10;
-
- Quaterniond q;
- Map<Quaterniond> qm(x.data()+5);
-
- // Static vector
- Vector3d v;
- v << 1,2,3;
- q = v2q(v);
- qm = v2q(v);
- std::cout << q.coeffs().transpose() << std::endl;
- std::cout << qm.coeffs().transpose() << std::endl;
-
- // Dynamic matrix
- Matrix<double, Dynamic, Dynamic> M(3,1);
- M << 1, 2, 3;
- q = v2q(M);
- std::cout << q.coeffs().transpose() << std::endl;
-
- // Dynamic vector segment
- x << 1,2,3,4,5,6,7,8,9,10;
- q = v2q(x.head(3));
- std::cout << q.coeffs().transpose() << std::endl;
-
- // Map over dynamic vector
- Map<VectorXd> m(x.data(), 3);
- q = v2q(m);
- std::cout << q.coeffs().transpose() << std::endl;
-
- // Float scalar
- Vector3f vf;
- Quaternionf qf;
- vf << 1,2,3;
- qf = v2q(vf);
- std::cout << qf.coeffs().transpose() << std::endl;
-
- // // Static assert at compile time
- // Vector2d v2;
- // q= v2q(v2);
- // std::cout << q.coeffs().transpose() << std::endl;
-
-}
diff --git a/demos/demo_factor_AHP.cpp b/demos/demo_factor_AHP.cpp
deleted file mode 100644
index bd1ad546d..000000000
--- a/demos/demo_factor_AHP.cpp
+++ /dev/null
@@ -1,148 +0,0 @@
-#include "base/math/pinhole_tools.h"
-#include "base/landmark/landmark_AHP.h"
-#include "base/factor/factor_AHP.h"
-#include "base/state_block/state_block.h"
-#include "base/state_block/state_quaternion.h"
-#include "base/sensor/sensor_camera.h"
-#include "base/capture/capture_image.h"
-
-int main()
-{
- using namespace wolf;
-
- std::cout << std::endl << "==================== factor AHP test ======================" << std::endl;
-
- TimeStamp t = 1;
-
- //=====================================================
- // Environment variable for configuration files
- std::string wolf_root = _WOLF_ROOT_DIR;
- std::cout << wolf_root << std::endl;
- //=====================================================
-
- // Wolf problem
- ProblemPtr wolf_problem_ptr_ = Problem::create("PO", 3);
-
- /* Do this while there aren't extrinsic parameters on the yaml */
- Eigen::Vector7s extrinsic_cam;
- extrinsic_cam.setRandom();
-// extrinsic_cam[0] = 0; //px
-// extrinsic_cam[1] = 0; //py
-// extrinsic_cam[2] = 0; //pz
-// extrinsic_cam[3] = 0; //qx
-// extrinsic_cam[4] = 0; //qy
-// extrinsic_cam[5] = 0; //qz
-// extrinsic_cam[6] = 1; //qw
- extrinsic_cam.tail<4>().normalize();
- std::cout << "========extrinsic_cam: " << extrinsic_cam.transpose() << std::endl;
- const Eigen::VectorXs extr = extrinsic_cam;
- /* Do this while there aren't extrinsic parameters on the yaml */
-
- SensorBasePtr sensor_ptr = wolf_problem_ptr_->installSensor("CAMERA", "PinHole", extr, wolf_root + "/src/examples/camera_params_ueye_radial_dist.yaml");
- SensorCameraPtr camera_ptr_ = std::static_pointer_cast<SensorCamera>(sensor_ptr);
-
- // PROCESSOR
- // one-liner API
- ProcessorBasePtr processor_ptr = wolf_problem_ptr_->installProcessor("IMAGE LANDMARK", "ORB", "PinHole", wolf_root + "/src/examples/processor_image_feature.yaml");
-
- // create the current frame
- Eigen::Vector7s frame_pos_ori;
- frame_pos_ori.setRandom();
-// frame_pos_ori[0] = 0; //px
-// frame_pos_ori[1] = 0; //py
-// frame_pos_ori[2] = 0; //pz
-// frame_pos_ori[3] = 0; //qx
-// frame_pos_ori[4] = 0; //qy
-// frame_pos_ori[5] = 0; //qz
-// frame_pos_ori[6] = 1; //qw
- frame_pos_ori.tail<4>().normalize();
- const Eigen::VectorXs frame_val = frame_pos_ori;
-
- FrameBasePtr last_frame = std::make_shared<FrameBase>(t,std::make_shared<StateBlock>(frame_val.head(3)), std::make_shared<StateQuaternion>(frame_val.tail(4)));
- std::cout << "Last frame" << std::endl;
- wolf_problem_ptr_->getTrajectory()->addFrame(last_frame);
-
- // Capture
- CaptureImagePtr image_ptr;
- t.setToNow();
- cv::Mat frame; //puede que necesite una imagen
-
- image_ptr = std::make_shared< CaptureImage>(t, camera_ptr_, frame);
- last_frame->addCapture(image_ptr);
-
- // create the feature
- cv::KeyPoint kp; kp.pt = {10,20};
- cv::Mat desc;
-
- FeaturePointImagePtr feat_point_image_ptr = std::make_shared<FeaturePointImage>(kp, 0, desc, Eigen::Matrix2s::Identity());
- image_ptr->addFeature(feat_point_image_ptr);
-
- FrameBasePtr anchor_frame = std::make_shared< FrameBase>(t,std::make_shared<StateBlock>(frame_val.head(3)), std::make_shared<StateQuaternion>(frame_val.tail(4)));
- //FrameBasePtr anchor_frame = wolf_problem_ptr_->getTrajectory()->getLastFrame();
-
- // create the landmark
- Eigen::Vector2s point2D;
- point2D[0] = feat_point_image_ptr->getKeypoint().pt.x;
- point2D[1] = feat_point_image_ptr->getKeypoint().pt.y;
- std::cout << "point2D: " << point2D.transpose() << std::endl;
-
- Scalar distance = 2; // arbitrary value
- Eigen::Vector4s vec_homogeneous;
-
- Eigen::VectorXs correction_vec = (std::static_pointer_cast<SensorCamera>(image_ptr->getSensor()))->getCorrectionVector();
- std::cout << "correction vector: " << correction_vec << std::endl;
- std::cout << "distortion vector: " << (std::static_pointer_cast<SensorCamera>(image_ptr->getSensor()))->getDistortionVector() << std::endl;
- point2D = pinhole::depixellizePoint(image_ptr->getSensor()->getIntrinsic()->getState(),point2D);
- std::cout << "point2D depixellized: " << point2D.transpose() << std::endl;
- point2D = pinhole::undistortPoint((std::static_pointer_cast<SensorCamera>(image_ptr->getSensor()))->getCorrectionVector(),point2D);
- std::cout << "point2D undistorted: " << point2D.transpose() << std::endl;
-
- Eigen::Vector3s point3D;
- point3D.head(2) = point2D;
- point3D(2) = 1;
-
- point3D.normalize();
- std::cout << "point3D normalized: " << point3D.transpose() << std::endl;
-
- vec_homogeneous = {point3D(0),point3D(1),point3D(2),1/distance};
- std::cout << "vec_homogeneous: " << vec_homogeneous.transpose() << std::endl;
-
- LandmarkAHPPtr landmark = std::make_shared<LandmarkAHP>(vec_homogeneous, anchor_frame, image_ptr->getSensor(), feat_point_image_ptr->getDescriptor());
-
- std::cout << "Landmark AHP created" << std::endl;
-
- // Create the factor
- FactorAHPPtr factor_ptr = std::make_shared<FactorAHP>(feat_point_image_ptr, std::static_pointer_cast<LandmarkAHP>(landmark), processor_ptr);
-
- feat_point_image_ptr->addFactor(factor_ptr);
- std::cout << "Factor AHP created" << std::endl;
-
- Eigen::Vector2s point2D_proj = point3D.head<2>()/point3D(2);
- std::cout << "point2D projected: " << point2D_proj.transpose() << std::endl;
-
- Eigen::Vector2s point2D_dist;
- point2D_dist = pinhole::distortPoint((std::static_pointer_cast<SensorCamera>(image_ptr->getSensor()))->getDistortionVector(),point2D_proj);
- std::cout << "point2D distorted: " << point2D_dist.transpose() << std::endl;
-
- Eigen::Vector2s point2D_pix;
- point2D_pix = pinhole::pixellizePoint(image_ptr->getSensor()->getIntrinsic()->getState(),point2D_dist);
- std::cout << "point2D pixellized: " << point2D_pix.transpose() << std::endl;
-
- Eigen::Vector2s expectation;
- Eigen::Vector3s current_frame_p = last_frame->getP()->getState();
- Eigen::Vector4s current_frame_o = last_frame->getO()->getState();
- Eigen::Vector3s anchor_frame_p = landmark->getAnchorFrame()->getP()->getState();
- Eigen::Vector4s anchor_frame_o = landmark->getAnchorFrame()->getO()->getState();
- Eigen::Vector4s landmark_ = landmark->getP()->getState();
-
- factor_ptr ->expectation(current_frame_p.data(), current_frame_o.data(),
- anchor_frame_p.data(), anchor_frame_o.data(),
- landmark_.data(), expectation.data());
-// current_frame p; current_frame o; anchor_frame p; anchor_frame o; homogeneous_vector landmark, residual
-
- std::cout << "expectation computed" << std::endl;
- std::cout << "expectation = " << expectation[0] << " " << expectation[1] << std::endl;
-
- return 0;
-
-}
diff --git a/demos/demo_factor_imu.cpp b/demos/demo_factor_imu.cpp
deleted file mode 100644
index 4040194b3..000000000
--- a/demos/demo_factor_imu.cpp
+++ /dev/null
@@ -1,279 +0,0 @@
-//Wolf
-#include "base/capture/capture_IMU.h"
-#include "base/processor/processor_IMU.h"
-#include "base/sensor/sensor_IMU.h"
-#include "base/capture/capture_pose.h"
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/factor/factor_odom_3D.h"
-#include "base/state_block/state_block.h"
-#include "base/state_block/state_quaternion.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-
-//#define DEBUG_RESULTS
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
- using std::shared_ptr;
- using std::make_shared;
- using std::static_pointer_cast;
-
- std::cout << std::endl << "==================== test_factor_imu ======================" << std::endl;
-
- bool c0(false), c1(false);// c2(true), c3(true), c4(true);
- // Wolf problem
- ProblemPtr wolf_problem_ptr_ = Problem::create("PQVBB 3D");
- Eigen::VectorXs IMU_extrinsics(7);
- IMU_extrinsics << 0,0,0, 0,0,0,1; // IMU pose in the robot
- SensorBasePtr sensor_ptr = wolf_problem_ptr_->installSensor("IMU", "Main IMU", IMU_extrinsics, shared_ptr<IntrinsicsBase>());
- wolf_problem_ptr_->installProcessor("IMU", "IMU pre-integrator", "Main IMU", "");
-
- // Ceres wrappers
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;ceres::LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- ceres_options.max_num_iterations = 1e4;
- CeresManager* ceres_manager_wolf_diff = new CeresManager(wolf_problem_ptr_, ceres_options, true);
-
- // Time and data variables
- TimeStamp t;
- Eigen::Vector6s data_;
- Scalar mpu_clock = 0;
-
- t.set(mpu_clock);
-
- // Set the origin
- Eigen::VectorXs x0(16);
- x0 << 0,0,0, 0,0,0,1, 0,0,0, 0,0,.001, 0,0,.002; // Try some non-zero biases
- wolf_problem_ptr_->getProcessorMotion()->setOrigin(x0, t); //this also creates a keyframe at origin
- wolf_problem_ptr_->getTrajectory()->getFrameList().front()->fix(); //fix the keyframe at origin
-
- TimeStamp ts(0);
- Eigen::VectorXs origin_state = x0;
-
- // Create one capture to store the IMU data arriving from (sensor / callback / file / etc.)
- CaptureIMUPtr imu_ptr( std::make_shared<CaptureIMU>(t, sensor_ptr, data_, Eigen::Matrix6s::Identity()) );
- imu_ptr->setFrame(wolf_problem_ptr_->getTrajectory()->getFrameList().back());
-
- // set variables
- using namespace std;
- Eigen::VectorXs state_vec;
- Eigen::VectorXs delta_preint;
- //FrameIMUPtr last_frame;
- Eigen::Matrix<wolf::Scalar,9,9> delta_preint_cov;
-
- //process data
- mpu_clock = 0.001003;
- //data_ << 0.579595, -0.143701, 9.939331, 0.127445, 0.187814, -0.055003;
- data_ << 0.0, 0.0, 9.81, 0.0, 0.0, 0.0;
- t.set(mpu_clock);
- // assign data to capture
- imu_ptr->setData(data_);
- imu_ptr->setTimeStamp(t);
- // process data in capture
- sensor_ptr->process(imu_ptr);
-
- if(c0){
- /// ******************************************************************************************** ///
- /// factor creation
- //create FrameIMU
- ts = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
- state_vec = wolf_problem_ptr_->getProcessorMotion()->getCurrentState();
- FrameIMUPtr last_frame = std::make_shared<FrameIMU>(KEY, ts, state_vec);
- wolf_problem_ptr_->getTrajectory()->addFrame(last_frame);
-
- //create a feature
- delta_preint_cov = wolf_problem_ptr_->getProcessorMotion()->getCurrentDeltaPreintCov();
- delta_preint = wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_;
- std::shared_ptr<FeatureIMU> feat_imu = std::make_shared<FeatureIMU>(delta_preint, delta_preint_cov);
- feat_imu->setCapture(imu_ptr);
-
- //create a factorIMU
- FactorIMUPtr factor_imu = std::make_shared<FactorIMU>(feat_imu, last_frame);
- feat_imu->addFactor(factor_imu);
- last_frame->addConstrainedBy(factor_imu);
-
- FrameIMUPtr ref_frame_ptr(std::static_pointer_cast<FrameIMU>(imu_ptr->getFrame()));
-
- Eigen::Matrix<wolf::Scalar, 10, 1> expect;
- Eigen::Vector3s ref_frame_p = ref_frame_ptr->getP()->getVector();
- Eigen::Quaternions ref_frame_o(ref_frame_ptr->getO()->getVector().data());
- Eigen::Vector3s ref_frame_v = ref_frame_ptr->getV()->getVector();
- Eigen::Vector3s current_frame_p = last_frame->getP()->getVector();
- Eigen::Quaternions current_frame_o(last_frame->getO()->getVector().data());
- Eigen::Vector3s current_frame_v = last_frame->getV()->getVector();
- Eigen::Vector3s acc_bias(ref_frame_ptr->getAccBias()->getVector()), gyro_bias(ref_frame_ptr->getGyroBias()->getVector());
- Eigen::Matrix<wolf::Scalar, 9, 1> residu;
- residu << 0,0,0, 0,0,0, 0,0,0;
-
- factor_imu->expectation(ref_frame_p, ref_frame_o, ref_frame_v, current_frame_p, current_frame_o, current_frame_v, expect);
- std::cout << "expectation : " << expect.transpose() << std::endl;
-
- factor_imu->getResiduals(ref_frame_p, ref_frame_o, ref_frame_v, acc_bias, gyro_bias, current_frame_p, current_frame_o, current_frame_v,residu);
- std::cout << "residuals : " << residu.transpose() << std::endl;
-
- //reset origin of motion to new frame
- wolf_problem_ptr_->getProcessorMotion()->setOrigin(last_frame);
- imu_ptr->setFrame(last_frame);
- }
- /// ******************************************************************************************** ///
-
- mpu_clock = 0.002135;
- //data_ << 0.581990, -0.191602, 10.071057, 0.136836, 0.203912, -0.057686;
- data_ << 0.0, 0.0, 9.81, 0.0, 0.0, 0.0;
- t.set(mpu_clock);
- imu_ptr->setData(data_);
- imu_ptr->setTimeStamp(t);
- sensor_ptr->process(imu_ptr);
-
- mpu_clock = 0.003040;
- //data_ << 0.596360, -0.225132, 10.205178, 0.154276, 0.174399, -0.036221;
- data_ << 0.0, 0.0, 9.81, 0.0, 0.0, 0.0;
- t.set(mpu_clock);
- imu_ptr->setData(data_);
- imu_ptr->setTimeStamp(t);
- sensor_ptr->process(imu_ptr);
-
- if(c1){
- /// ******************************************************************************************** ///
- /// factor creation
- //create FrameIMU
- ts = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
- state_vec = wolf_problem_ptr_->getProcessorMotion()->getCurrentState();
- FrameIMUPtr last_frame = std::make_shared<FrameIMU>(KEY, ts, state_vec);
- wolf_problem_ptr_->getTrajectory()->addFrame(last_frame);
-
- //create a feature
- delta_preint_cov = wolf_problem_ptr_->getProcessorMotion()->getCurrentDeltaPreintCov();
- delta_preint = wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_;
- std::shared_ptr<FeatureIMU> feat_imu = std::make_shared<FeatureIMU>(delta_preint, delta_preint_cov);
- feat_imu->setCapture(imu_ptr);
-
- //create a factorIMU
- FactorIMUPtr factor_imu = std::make_shared<FactorIMU>(feat_imu, last_frame);
- feat_imu->addFactor(factor_imu);
- last_frame->addConstrainedBy(factor_imu);
-
- FrameIMUPtr ref_frame_ptr(std::static_pointer_cast<FrameIMU>(imu_ptr->getFrame()));
-
- Eigen::Matrix<wolf::Scalar, 10, 1> expect;
- Eigen::Vector3s ref_frame_p = ref_frame_ptr->getP()->getVector();
- Eigen::Quaternions ref_frame_o(ref_frame_ptr->getO()->getVector().data());
- Eigen::Vector3s ref_frame_v = ref_frame_ptr->getV()->getVector();
- Eigen::Vector3s current_frame_p = last_frame->getP()->getVector();
- Eigen::Quaternions current_frame_o(last_frame->getO()->getVector().data());
- Eigen::Vector3s current_frame_v = last_frame->getV()->getVector();
- Eigen::Vector3s acc_bias(ref_frame_ptr->getAccBias()->getVector()), gyro_bias(ref_frame_ptr->getGyroBias()->getVector());
- Eigen::Matrix<wolf::Scalar, 9, 1> residu;
- residu << 0,0,0, 0,0,0, 0,0,0;
-
- factor_imu->expectation(ref_frame_p, ref_frame_o, ref_frame_v, acc_bias, gyro_bias, current_frame_p, current_frame_o, current_frame_v, expect);
- std::cout << "expectation : " << expect.transpose() << std::endl;
-
- factor_imu->getResiduals(ref_frame_p, ref_frame_o, ref_frame_v, acc_bias, gyro_bias, current_frame_p, current_frame_o, current_frame_v,residu);
- std::cout << "residuals : " << residu.transpose() << std::endl;
-
- //reset origin of motion to new frame
- wolf_problem_ptr_->getProcessorMotion()->setOrigin(last_frame);
- imu_ptr->setFrame(last_frame);
- }
-
- mpu_clock = 0.004046;
- //data_ << 0.553250, -0.203577, 10.324929, 0.128787, 0.156959, -0.044270;
- data_ << 0.0, 0.0, 9.81, 0.0, 0.0, 0.0;
- t.set(mpu_clock);
- imu_ptr->setData(data_);
- imu_ptr->setTimeStamp(t);
- sensor_ptr->process(imu_ptr);
-
- mpu_clock = 0.005045;
- //data_ << 0.548459, -0.184417, 10.387200, 0.083175, 0.120738, -0.026831;
- data_ << 0.0, 0.0, 9.81, 0.0, 0.0, 0.0;
- t.set(mpu_clock);
- imu_ptr->setData(data_);
- imu_ptr->setTimeStamp(t);
- sensor_ptr->process(imu_ptr);
-
- //create the factor
- //create FrameIMU
- ts = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
- state_vec = wolf_problem_ptr_->getProcessorMotion()->getCurrentState();
- FrameIMUPtr last_frame = std::make_shared<FrameIMU>(KEY, ts, state_vec);
- wolf_problem_ptr_->getTrajectory()->addFrame(last_frame);
-
- //create a feature
- delta_preint_cov = wolf_problem_ptr_->getProcessorMotion()->getCurrentDeltaPreintCov();
- delta_preint = wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_;
- std::shared_ptr<FeatureIMU> feat_imu = std::make_shared<FeatureIMU>(delta_preint, delta_preint_cov);
- feat_imu->setCapture(imu_ptr);
-
- //create a factorIMU
- FactorIMUPtr factor_imu = std::make_shared<FactorIMU>(feat_imu, last_frame);
- feat_imu->addFactor(factor_imu);
- last_frame->addConstrainedBy(factor_imu);
-
- FrameIMUPtr ref_frame_ptr(std::static_pointer_cast<FrameIMU>(imu_ptr->getFrame()));
-
- Eigen::Matrix<wolf::Scalar, 10, 1> expect;
- Eigen::Vector3s ref_frame_p = ref_frame_ptr->getP()->getVector();
- Eigen::Quaternions ref_frame_o(ref_frame_ptr->getO()->getVector().data());
- Eigen::Vector3s ref_frame_v = ref_frame_ptr->getV()->getVector();
- Eigen::Vector3s current_frame_p = last_frame->getP()->getVector();
- Eigen::Quaternions current_frame_o(last_frame->getO()->getVector().data());
- Eigen::Vector3s current_frame_v = last_frame->getV()->getVector();
- Eigen::Vector3s acc_bias(ref_frame_ptr->getAccBias()->getVector()), gyro_bias(ref_frame_ptr->getGyroBias()->getVector());
- Eigen::Matrix<wolf::Scalar, 9, 1> residu;
- residu << 0,0,0, 0,0,0, 0,0,0;
-
- factor_imu->expectation(ref_frame_p, ref_frame_o, ref_frame_v, acc_bias, gyro_bias, current_frame_p, current_frame_o, current_frame_v, expect);
- std::cout << "expectation : " << expect.transpose() << std::endl;
-
- factor_imu->getResiduals(ref_frame_p, ref_frame_o, ref_frame_v, acc_bias, gyro_bias, current_frame_p, current_frame_o, current_frame_v,residu);
- std::cout << "residuals : " << residu.transpose() << std::endl;
-
- if(wolf_problem_ptr_->check(1)){
- wolf_problem_ptr_->print(4,1,1,1);
- }
-
- ///having a look at covariances
- Eigen::MatrixXs predelta_cov;
- predelta_cov.resize(9,9);
- predelta_cov = wolf_problem_ptr_->getProcessorMotion()->getCurrentDeltaPreintCov();
- //std::cout << "predelta_cov : \n" << predelta_cov << std::endl;
-
- ///Optimization
- // PRIOR
- //FrameBasePtr first_frame = wolf_problem_ptr_->getTrajectory()->getFrameList().front();
- wolf_problem_ptr_->getProcessorMotion()->setOrigin(wolf_problem_ptr_->getTrajectory()->getFrameList().front());
- //SensorBasePtr sensorbase = std::make_shared<SensorBase>("ABSOLUTE POSE", nullptr, nullptr, nullptr, 0);
- //CapturePosePtr initial_covariance = std::make_shared<CaptureFix>(TimeStamp(0), sensorbase, first_frame->getState().head(7), Eigen::Matrix6s::Identity() * 0.01);
- //first_frame->addCapture(initial_covariance);
- //initial_covariance->process();
- //std::cout << "initial covariance: factor " << initial_covariance->getFeatureList().front()->getConstrainedByList().front()->id() << std::endl << initial_covariance->getFeatureList().front()->getMeasurementCovariance() << std::endl;
-
- // COMPUTE COVARIANCES
- std::cout << "computing covariances..." << std::endl;
- ceres_manager_wolf_diff->computeCovariances(ALL_MARGINALS);//ALL_MARGINALS, ALL
- std::cout << "computed!" << std::endl;
-
- /*
- // SOLVING PROBLEMS
- ceres::Solver::Summary summary_diff;
- std::cout << "solving..." << std::endl;
- Eigen::VectorXs prev_wolf_state = wolf_problem_ptr_->getTrajectory()->getFrameList().back()->getState();
- summary_diff = ceres_manager_wolf_diff->solve();
- Eigen::VectorXs post_wolf_state = wolf_problem_ptr_->getTrajectory()->getFrameList().back()->getState();
- std::cout << " prev_wolf_state : " << prev_wolf_state.transpose() << "\n post_wolf_state : " << post_wolf_state.transpose() << std::endl;
- //std::cout << summary_wolf_diff.BriefReport() << std::endl;
- std::cout << "solved!" << std::endl;
- */
-
- /*
- std::cout << "WOLF AUTO DIFF" << std::endl;
- std::cout << "Jacobian evaluation: " << summary_wolf.jacobian_evaluation_time_in_seconds << std::endl;
- std::cout << "Total time: " << summary_wolf.total_time_in_seconds << std::endl;
- */
-
- return 0;
-}
diff --git a/demos/demo_factor_odom_3D.cpp b/demos/demo_factor_odom_3D.cpp
deleted file mode 100644
index be7a81c4f..000000000
--- a/demos/demo_factor_odom_3D.cpp
+++ /dev/null
@@ -1,13 +0,0 @@
-/*
- * test_factor_odom_3D.cpp
- *
- * Created on: Oct 7, 2016
- * Author: jsola
- */
-
-#include "core/factor/factor_odom_3D.h"
-
-namespace wolf
-{
-
-} /* namespace wolf */
diff --git a/demos/demo_faramotics_simulation.cpp b/demos/demo_faramotics_simulation.cpp
deleted file mode 100644
index e095e561d..000000000
--- a/demos/demo_faramotics_simulation.cpp
+++ /dev/null
@@ -1,244 +0,0 @@
-//std includes
-#include <cstdlib>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// Eigen includes
-#include <eigen3/Eigen/Dense>
-#include <eigen3/Eigen/Geometry>
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-// wolf
-#include "base/common/wolf.h"
-#include "base/feature/feature_base.h"
-#include "base/landmark/landmark_base.h"
-#include "base/state_block/state_block.h"
-
-//faramotics includes
-#include "faramotics/dynamicSceneRender.h"
-#include "faramotics/rangeScan2D.h"
-#include "btr-headers/pose3d.h"
-
-namespace wolf {
-class FaramoticsRobot
-{
- public:
-
- Cpose3d viewPoint, devicePose, laser1Pose, laser2Pose, estimated_vehicle_pose, estimated_laser_1_pose, estimated_laser_2_pose;
- vector < Cpose3d > devicePoses;
- vector<float> scan1, scan2;
- string modelFileName;
- CrangeScan2D* myScanner;
- CdynamicSceneRender* myRender;
- Eigen::Vector3s ground_truth_pose_;
- Eigen::Vector4s laser_1_pose_, laser_2_pose_;
-
- FaramoticsRobot(int argc, char** argv, const Eigen::Vector4s& _laser_1_pose, const Eigen::Vector4s& _laser_2_pose) :
- modelFileName("/home/jvallve/iri-lab/faramotics/models/campusNordUPC.obj"),
- laser_1_pose_(_laser_1_pose),
- laser_2_pose_(_laser_2_pose)
- {
- devicePose.setPose(2, 8, 0.2, 0, 0, 0);
- viewPoint.setPose(devicePose);
- viewPoint.moveForward(10);
- viewPoint.rt.setEuler(viewPoint.rt.head() + M_PI / 2, viewPoint.rt.pitch() + 30. * M_PI / 180., viewPoint.rt.roll());
- viewPoint.moveForward(-15);
- //glut initialization
- faramotics::initGLUT(argc, argv);
- //create a viewer for the 3D model and scan points
- myRender = new CdynamicSceneRender(1200, 700, 90 * M_PI / 180, 90 * 700.0 * M_PI / (1200.0 * 180.0), 0.2, 100);
- myRender->loadAssimpModel(modelFileName, true); //with wireframe
- //create scanner and load 3D model
- myScanner = new CrangeScan2D(HOKUYO_UTM30LX_180DEG); //HOKUYO_UTM30LX_180DEG or LEUZE_RS4
- myScanner->loadAssimpModel(modelFileName);
- }
-
- //function travel around
- Eigen::Vector3s motionCampus(unsigned int ii, double& displacement_, double& rotation_)
- {
- if (ii <= 120){ displacement_ = 0.1; rotation_ = 0; }
- else if (ii <= 170) { displacement_ = 0.2; rotation_ = 1.8 * M_PI / 180; }
- else if (ii <= 220) { displacement_ = 0; rotation_ =-1.8 * M_PI / 180; }
- else if (ii <= 310) { displacement_ = 0.1; rotation_ = 0; }
- else if (ii <= 487) { displacement_ = 0.1; rotation_ =-1.0 * M_PI / 180; }
- else if (ii <= 600) { displacement_ = 0.2; rotation_ = 0; }
- else if (ii <= 700) { displacement_ = 0.1; rotation_ =-1.0 * M_PI / 180; }
- else if (ii <= 780) { displacement_ = 0; rotation_ =-1.0 * M_PI / 180; }
- else { displacement_ = 0.3; rotation_ = 0; }
-
- devicePose.moveForward(displacement_);
- devicePose.rt.setEuler(devicePose.rt.head() + rotation_, devicePose.rt.pitch(), devicePose.rt.roll());
-
- // laser 1
- laser1Pose.setPose(devicePose);
- laser1Pose.moveForward(laser_1_pose_(0));
- // laser 2
- laser2Pose.setPose(devicePose);
- laser2Pose.moveForward(laser_2_pose_(0));
- laser2Pose.rt.setEuler(laser2Pose.rt.head() + laser_2_pose_(3), laser2Pose.rt.pitch(), laser2Pose.rt.roll());
-
- devicePoses.push_back(devicePose);
-
- ground_truth_pose_ << devicePose.pt(0), devicePose.pt(1), devicePose.rt.head();
- return ground_truth_pose_;
- }
-
- ~FaramoticsRobot()
- {
- std::cout << "deleting render and scanner.." << std::endl;
- delete myRender;
- delete myScanner;
- std::cout << "deleted!" << std::endl;
- }
-
- //compute scans
- vector<float> computeScan(const int scan_id)
- {
- if (scan_id == 1)
- {
- scan1.clear();
- myScanner->computeScan(laser1Pose, scan1);
- return scan1;
- }
- else
- {
- scan2.clear();
- myScanner->computeScan(laser2Pose, scan2);
- return scan2;
- }
- }
-
- void render(const FeatureBasePtrList& feature_list, int laser, const LandmarkBasePtrList& landmark_list, const Eigen::Vector3s& estimated_pose)
- {
- // detected corners
- //std::cout << " drawCorners: " << feature_list.size() << std::endl;
- std::vector<double> corner_vector;
- corner_vector.reserve(2*feature_list.size());
- for (auto corner : feature_list)
- {
- //std::cout << " corner " << corner->id() << std::endl;
- corner_vector.push_back(corner->getMeasurement(0));
- corner_vector.push_back(corner->getMeasurement(1));
- }
- myRender->drawCorners(laser == 1 ? laser1Pose : laser2Pose, corner_vector);
-
- // landmarks
- //std::cout << " drawLandmarks: " << landmark_list.size() << std::endl;
- std::vector<double> landmark_vector;
- landmark_vector.reserve(3*landmark_list.size());
- for (auto landmark : landmark_list)
- {
- Scalar* position_ptr = landmark->getP()->get();
- landmark_vector.push_back(*position_ptr); //x
- landmark_vector.push_back(*(position_ptr + 1)); //y
- landmark_vector.push_back(0.2); //z
- }
- myRender->drawLandmarks(landmark_vector);
-
- // draw localization and sensors
- estimated_vehicle_pose.setPose(estimated_pose(0), estimated_pose(1), 0.2, estimated_pose(2), 0, 0);
- estimated_laser_1_pose.setPose(estimated_vehicle_pose);
- estimated_laser_1_pose.moveForward(laser_1_pose_(0));
- estimated_laser_2_pose.setPose(estimated_vehicle_pose);
- estimated_laser_2_pose.moveForward(laser_2_pose_(0));
- estimated_laser_2_pose.rt.setEuler(estimated_laser_2_pose.rt.head() + laser_2_pose_(3), estimated_laser_2_pose.rt.pitch(), estimated_laser_2_pose.rt.roll());
- myRender->drawPoseAxisVector( { estimated_vehicle_pose, estimated_laser_1_pose, estimated_laser_2_pose });
-
- //Set view point and render the scene
- //locate visualization view point, somewhere behind the device
- // viewPoint.setPose(devicePose);
- // viewPoint.rt.setEuler( viewPoint.rt.head(), viewPoint.rt.pitch()+20.*M_PI/180., viewPoint.rt.roll() );
- // viewPoint.moveForward(-5);
- myRender->setViewPoint(viewPoint);
- myRender->drawPoseAxis(devicePose);
- myRender->drawScan(laser == 1 ? laser1Pose : laser2Pose, laser == 1 ? scan1 : scan2, 180. * M_PI / 180., 90. * M_PI / 180.); //draw scan
- myRender->render();
- }
-};
-}
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- std::cout << "\n============================================================\n";
- std::cout << "========== 2D Robot with odometry and 2 LIDARs =============\n";
-
- unsigned int n_execution = 900; //number of iterations of the whole execution
-
- // VARIABLES ============================================================================================
- Eigen::Vector2s odom_data;
- Eigen::Vector3s ground_truth;
- Scalar dt = 0.05;
-
- // Laser params
- Eigen::Vector4s laser_1_pose, laser_2_pose; //xyz + theta
- laser_1_pose << 1.2, 0, 0, 0; //laser 1
- laser_2_pose << -1.2, 0, 0, M_PI; //laser 2
- Eigen::VectorXs laser_params(8);
- laser_params << M_PI/2, -M_PI/2, -M_PI/720, 0.01, 0.2, 100, 0.01, 0.01;
- std::vector<float> scan1, scan2;
-
- // Simulated robot
- FaramoticsRobot robot(argc, argv, laser_1_pose, laser_2_pose);
-
- // Initial pose
- ground_truth << 2, 8, 0;
-
- //output file
- std::ofstream laser_1_file, laser_2_file, odom_file, groundtruth_file;
- groundtruth_file.open("simulated_groundtruth.txt", std::ofstream::out); //open log file
- odom_file.open("simulated_odom.txt", std::ofstream::out); //open log file
- laser_1_file.open("simulated_laser_1.txt", std::ofstream::out); //open log file
- laser_2_file.open("simulated_laser_2.txt", std::ofstream::out); //open log file
-
- // write laser params
- laser_1_file << 0 << " " << laser_params.transpose() << " " << robot.myScanner->getNumPoints() << std::endl;
- laser_2_file << 0 << " " << laser_params.transpose() << " " << robot.myScanner->getNumPoints() << std::endl;
- laser_1_file << 0 << " " << laser_1_pose.transpose() << std::endl;
- laser_2_file << 0 << " " << laser_2_pose.transpose() << std::endl;
-
- // origin frame groundtruth
- groundtruth_file << 0 << " " << ground_truth.transpose() << std::endl;
-
- //std::cout << "START TRAJECTORY..." << std::endl;
- // START TRAJECTORY ============================================================================================
- for (unsigned int step = 1; step < n_execution; step++)
- {
- // ROBOT MOVEMENT ---------------------------
- ground_truth = robot.motionCampus(step, odom_data(0), odom_data(1));
-
- // LIDAR DATA ---------------------------
- scan1 = robot.computeScan(1);
- scan2 = robot.computeScan(2);
-
- // writing files ---------------------------
- groundtruth_file << step*dt << " " << ground_truth.transpose() << std::endl;
- odom_file << step*dt << " " << odom_data.transpose() << std::endl;
- laser_1_file << step*dt << " ";
- for (auto range : scan1)
- laser_1_file << range << " ";
- laser_1_file << std::endl;
- laser_2_file << step*dt << " ";
- for (auto range : scan1)
- laser_2_file << range << " ";
- laser_2_file << std::endl;
- }
-
- groundtruth_file.close(); //close log file
- odom_file.close(); //close log file
- laser_1_file.close(); //close log file
- laser_2_file.close(); //close log file
-
- std::cout << " ========= END ===========" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_fcn_ptr.cpp b/demos/demo_fcn_ptr.cpp
deleted file mode 100644
index 8ca82790e..000000000
--- a/demos/demo_fcn_ptr.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/*
- * test_fcn_ptr.cpp
- *
- * Created on: Nov 29, 2016
- * Author: jsola
- */
-
-#include <iostream>
-#include <cstdarg>
-
-// define some fcns with differnt # of args
-double half (double _a) { return _a/2; }
-double quarter (double _a) { return _a/4; }
-double divide (double _n, double _d) { return _n/_d; }
-double mult (double _x, double _y) { return _x*_y; }
-double mult_div (double _x, double _y, double _z) { return _x*_y/_z; }
-
-//======== test_simple usage of function pointers ============
-typedef double (*FcnType)(double);
-
-double run_simple(FcnType f, double a){ return f(a); }
-
-void test_simple()
-{
- std::cout << "simple..." << std::endl;
- std::cout << "4/2 = " << run_simple(half, 4) << std::endl;
- std::cout << "4/4 = " << run_simple(quarter, 4) << std::endl;
-}
-
-//======== more usage of function pointers ============
-typedef double (*FcnType2)(double a, double b);
-typedef double (*FcnType3)(double a, double b, double c);
-
-double run_2(FcnType2 f, double a, double b) { return f(a, b); }
-double run_3(FcnType3 f, double a, double b, double c) { return f(a, b, c); }
-
-void test_more()
-{
- std::cout << "more..." << std::endl;
- std::cout << "4/2 = " << run_2(divide, 4, 2) << std::endl;
- std::cout << "4*2 = " << run_2(mult, 4, 2) << std::endl;
- std::cout << "4*3/6 = " << run_3(mult_div, 4, 3, 6) << std::endl;
-}
-
-//======== variadic usage of function pointers =========
-typedef double (*FcnTypeV)(...);
-
-// we will try to use half(), quarter(), mult(), divide() and mult_div() above
-
-//------------------------------------------------------------------------------------
-// ---- try just to read the args of the variadic fcn; no function pointer yet
-double run_v_dummy(int n, ...)
-{
- va_list args;
- va_start(args, n);
- double b = 0;
- for (int i=0; i<n; i++)
- b += va_arg(args, double);
- return b;
-}
-
-void test_var_dummy()
-{
- std::cout << "var dummy..." << std::endl;
- std::cout << "1 = " << run_v_dummy(1, 1.0) << std::endl;
- std::cout << "1+2 = " << run_v_dummy(2, 1.0, 2.0) << std::endl;
- std::cout << "1+2+3 = " << run_v_dummy(3, 1.0, 2.0, 3.0) << std::endl;
-}
-
-//------------------------------------------------------------------------------------
-// ---- call function through pointer; ugly solution with switch / case on the # of args:
-double run_v_switch(FcnTypeV f, int n, ...)
-{
- va_list args ;
- va_start(args, n); // args start after n
- switch (n)
- {
- case 1:
- return f(va_arg(args, double));
- break;
- case 2:
- return f(va_arg(args, double), va_arg(args, double));
- break;
- case 3:
- return f(va_arg(args, double), va_arg(args, double), va_arg(args, double));
- break;
- default:
- return 0;
- }
-}
-
-void test_var_switch()
-{
- std::cout << "var using switch/case of the # of args (ugly)..." << std::endl;
- std::cout << "4/2 = " << run_v_switch((FcnTypeV)half, 1, 4.0 ) << std::endl;
- std::cout << "4/4 = " << run_v_switch((FcnTypeV)quarter, 1, 4.0 ) << std::endl;
- std::cout << "4/2 = " << run_v_switch((FcnTypeV)divide, 2, 4.0, 2.0 ) << std::endl;
- std::cout << "4*2 = " << run_v_switch((FcnTypeV)mult, 2, 4.0, 2.0 ) << std::endl;
- std::cout << "4*3/6 = " << run_v_switch((FcnTypeV)mult_div, 3, 4.0, 3.0, 6.0) << std::endl;
-}
-
-//------------------------------------------------------------------------------------
-// ---- call function through pointer; try to forward all args straight into the inner function!
-double run_v(FcnTypeV f, int n, ...)
-{
- va_list args;
- va_start(args,n); // args start after n
- return f(args); // hop!
-}
-
-void test_var()
-{
- std::cout << "var forwarding all args to the inner fcn (nice!)..." << std::endl;
- std::cout << "4/2 = " << run_v((FcnTypeV)half, 1, 4.0 ) << std::endl;
- std::cout << "4/4 = " << run_v((FcnTypeV)quarter, 1, 4.0 ) << std::endl;
- std::cout << "4/2 = " << run_v((FcnTypeV)divide, 2, 4.0, 2.0 ) << std::endl;
- std::cout << "4*2 = " << run_v((FcnTypeV)mult, 2, 4.0, 2.0 ) << std::endl;
- std::cout << "4*3/6 = " << run_v((FcnTypeV)mult_div, 3, 4.0, 3.0, 6.0) << std::endl;
-}
-
-//####################################################################################
-
-int main()
-{
- test_simple();
- test_more();
- test_var_dummy();
- test_var_switch();
- test_var();
-}
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diff --git a/demos/demo_image.cpp b/demos/demo_image.cpp
deleted file mode 100644
index 3997b9476..000000000
--- a/demos/demo_image.cpp
+++ /dev/null
@@ -1,177 +0,0 @@
-// Testing things for the 3D image odometry
-
-//Wolf includes
-#include "core/sensor/sensor_camera.h"
-#include "core/capture/capture_image.h"
-#include "core/processor/processor_tracker_feature_image.h"
-#include "core/ceres_wrapper/ceres_manager.h"
-
-// Vision utils includes
-#include <vision_utils.h>
-#include <sensors.h>
-#include <common_class/buffer.h>
-#include <common_class/frame.h>
-
-//std includes
-#include <ctime>
-#include <iostream>
-#include <string>
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
- using std::shared_ptr;
- using std::make_shared;
- using std::static_pointer_cast;
-
- //ProcessorImageFeature test
- std::cout << std::endl << " ========= ProcessorImageFeature test ===========" << std::endl << std::endl;
-
- // Sensor or sensor recording
- vision_utils::SensorCameraPtr sen_ptr = vision_utils::askUserSource(argc, argv);
- if (sen_ptr==NULL)
- return 0;
-
- unsigned int buffer_size = 8;
- vision_utils::Buffer<vision_utils::FramePtr> frame_buff(buffer_size);
- frame_buff.add( vision_utils::setFrame(sen_ptr->getImage(), 0) );
-
- unsigned int img_width = frame_buff.back()->getImage().cols;
- unsigned int img_height = frame_buff.back()->getImage().rows;
- std::cout << "Image size: " << img_width << "x" << img_height << std::endl;
-
- // graphics
- cv::namedWindow("Feature tracker"); // Creates a window for display.
- cv::moveWindow("Feature tracker", 0, 0);
- cv::startWindowThread();
-
- CaptureImagePtr image_ptr;
-
- TimeStamp t = 1;
-
- std::string wolf_root = _WOLF_ROOT_DIR;
- std::cout << "Wolf root: " << wolf_root << std::endl;
-
- ProblemPtr wolf_problem_ = Problem::create("PO", 3);
-
- //=====================================================
- // Method 1: Use data generated here for sensor and processor
- //=====================================================
-
-// // SENSOR
-// Eigen::Vector4s k = {320,240,320,320};
-// SensorCameraPtr camera_ptr = std::make_shared<SensorCamera>(std::make_shared<StateBlock>(Eigen::Vector3s::Zero()),
-// std::make_shared<StateBlock>(Eigen::Vector3s::Zero()),
-// std::make_shared<StateBlock>(k,false),img_width,img_height);
-//
-// wolf_problem_->getHardware()->addSensor(camera_ptr);
-//
-// // PROCESSOR
-// ProcessorParamsImage tracker_params;
-// tracker_params.matcher.min_normalized_score = 0.75;
-// tracker_params.matcher.similarity_norm = cv::NORM_HAMMING;
-// tracker_params.matcher.roi_width = 30;
-// tracker_params.matcher.roi_height = 30;
-// tracker_params.active_search.grid_width = 12;
-// tracker_params.active_search.grid_height = 8;
-// tracker_params.active_search.separation = 1;
-// tracker_params.max_new_features =0;
-// tracker_params.min_features_for_keyframe = 20;
-//
-// DetectorDescriptorParamsOrb orb_params;
-// orb_params.type = DD_ORB;
-//
-// DetectorDescriptorParamsBrisk brisk_params;
-// brisk_params.type = DD_BRISK;
-//
-// // select the kind of detector-descriptor parameters
-// tracker_params.detector_descriptor_params_ptr = std::make_shared<DetectorDescriptorParamsOrb>(orb_params); // choose ORB
-//// tracker_params.detector_descriptor_params_ptr = std::make_shared<DetectorDescriptorParamsBrisk>(brisk_params); // choose BRISK
-//
-// std::cout << tracker_params.detector_descriptor_params_ptr->type << std::endl;
-//
-// ProcessorTrackerTrifocalTensorPtr prc_image = std::make_shared<ProcessorImageFeature>(tracker_params);
-//// camera_ptr->addProcessor(prc_image);
-// std::cout << "sensor & processor created and added to wolf problem" << std::endl;
- //=====================================================
-
- //=====================================================
- // Method 2: Use factory to create sensor and processor
- //=====================================================
-
- /* Do this while there aren't extrinsic parameters on the yaml */
- Eigen::Vector7s extrinsic_cam;
- extrinsic_cam[0] = 0; //px
- extrinsic_cam[1] = 0; //py
- extrinsic_cam[2] = 0; //pz
- extrinsic_cam[3] = 0; //qx
- extrinsic_cam[4] = 0; //qy
- extrinsic_cam[5] = 0; //qz
- extrinsic_cam[6] = 1; //qw
- std::cout << "========extrinsic_cam: " << extrinsic_cam.transpose() << std::endl;
- const Eigen::VectorXs extr = extrinsic_cam;
- /* Do this while there aren't extrinsic parameters on the yaml */
-
- // SENSOR
- // one-liner API
- SensorBasePtr sensor_ptr = wolf_problem_->installSensor("CAMERA", "PinHole", Eigen::VectorXs::Zero(7), wolf_root + "/src/examples/camera_params_ueye_sim.yaml");
- SensorCameraPtr camera_ptr = static_pointer_cast<SensorCamera>(sensor_ptr);
- camera_ptr->setImgWidth(img_width);
- camera_ptr->setImgHeight(img_height);
-
- // PROCESSOR
- // one-liner API
- ProcessorTrackerFeatureImagePtr prc_img_ptr = std::static_pointer_cast<ProcessorTrackerFeatureImage>( wolf_problem_->installProcessor("IMAGE FEATURE", "ORB", "PinHole", wolf_root + "/src/examples/processor_image_feature.yaml") );
- std::cout << "sensor & processor created and added to wolf problem" << std::endl;
- //=====================================================
-
-// // Ceres wrapper
-// ceres::Solver::Options ceres_options;
-// ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
-// ceres_options.max_line_search_step_contraction = 1e-3;
-// // ceres_options.minimizer_progress_to_stdout = false;
-// // ceres_options.line_search_direction_type = ceres::LBFGS;
-// // ceres_options.max_num_iterations = 100;
-// google::InitGoogleLogging(argv[0]);
-// CeresManager ceres_manager(wolf_problem_, ceres_options);
-
- for(int f = 0; f<10000; ++f)
- {
- frame_buff.add( vision_utils::setFrame(sen_ptr->getImage(), f) );
-
- std::cout << "\n=============== Frame #: " << f << " ===============" << std::endl;
-
- t.setToNow();
- clock_t t1 = clock();
-
- // Preferred method with factory objects:
- image_ptr = make_shared<CaptureImage>(t, camera_ptr, frame_buff.back()->getImage());
-
- camera_ptr->process(image_ptr);
-
- std::cout << "Time: " << ((double) clock() - t1) / CLOCKS_PER_SEC << "s" << std::endl;
-
- wolf_problem_->print();
-
- cv::Mat image = frame_buff.back()->getImage().clone();
- prc_img_ptr->drawFeatures(image);
- prc_img_ptr->drawRoi(image,prc_img_ptr->detector_roi_,cv::Scalar(0.0,255.0, 255.0)); //active search roi
- prc_img_ptr->drawRoi(image,prc_img_ptr->tracker_roi_, cv::Scalar(255.0, 0.0, 255.0)); //tracker roi
- prc_img_ptr->drawTarget(image,prc_img_ptr->tracker_target_);
- cv::imshow("Feature tracker", image);
- cv::waitKey(1);
-
-// if((f%100) == 0)
-// {
-// std::string summary = ceres_manager.solve(2);
-// std::cout << summary << std::endl;
-//
-// std::cout << "Last key frame pose: "
-// << wolf_problem_->getLastKeyFrame()->getP()->getState().transpose() << std::endl;
-// std::cout << "Last key frame orientation: "
-// << wolf_problem_->getLastKeyFrame()->getO()->getState().transpose() << std::endl;
-//
-// cv::waitKey(0);
-// }
- }
-}
diff --git a/demos/demo_imuDock.cpp b/demos/demo_imuDock.cpp
deleted file mode 100644
index dab6894d7..000000000
--- a/demos/demo_imuDock.cpp
+++ /dev/null
@@ -1,318 +0,0 @@
-/**
- * \file test_imuDock.cpp
- *
- * Created on: July 18, 2017
- * \author: Dinesh Atchuthan
- */
-
-#include "base/processor/processor_IMU.h"
-#include "base/sensor/sensor_IMU.h"
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-#include "base/sensor/sensor_odom_3D.h"
-#include "base/processor/processor_odom_3D.h"
-
-//Factors headers
-#include "base/factor/factor_fix_bias.h"
-
-//std
-#include <iostream>
-#include <fstream>
-#include "base/factor/factor_pose_3D.h"
-
-#define OUTPUT_RESULTS
-//#define ADD_KF3
-
-/* OFFLINE VERSION
- In this test, we use the experimental conditions needed for Humanoids 2017.
- IMU data are acquired using the docking station.
-
- Factors are (supposing to KeyFrames, stateblocks or first Keyframe are noted *1 and second Keyframes's are *2) :
- invar : P1, V1, V2
- var : Q1,B1,P2,Q2,B2
- factors : Odometry factor between KeyFrames
- IMU factor
- FixBias factor --> makes the problem observable (adding a big covariance on all part but a smaller one on yaw)
- Fix3D factor
-
- What we expect : Estimate biases (this will strongly depend on the actual trajectory of the IMU)
- Estimate the position and orienttion of the IMU (check with the standard deviation using covariance matrix)
-
- Representation of the application:
-
- Imu
- KF1----------â—¼----------KF2
- /----P1----------\ /----------P2 invar : P1, V1, V2
- Abs|------â—¼ â—¼ var : Q1,B1,P2,Q2,B2
- \----Q1----------/ \----------Q2
- V1 Odom
- Abs|------â—¼-----B1
-*/
-int main(int argc, char** argv)
-{
- //#################################################### INITIALIZATION
- using namespace wolf;
-
- //___get input file for imu data___
- std::ifstream imu_data_input;
- const char * filename_imu;
- if (argc < 02)
- {
- WOLF_ERROR("Missing 1 input argument (path to imu data file).")
- return 1; //return with error
- }
- else
- {
- filename_imu = argv[1];
-
- imu_data_input.open(filename_imu);
- WOLF_INFO("imu file : ", filename_imu)
- }
-
- // ___Check if the file is correctly opened___
- if(!imu_data_input.is_open()){
- WOLF_ERROR("Failed to open data file ! Exiting")
- return 1;
- }
-
- #ifdef OUTPUT_RESULTS
- //define output file
- std::ofstream output_results_before, output_results_after, checking;
- output_results_before.open("imu_dock_beforeOptim.dat");
- output_results_after.open("imu_dock_afterOptim.dat");
- checking.open("KF_pose_stdev.dat");
- #endif
-
- // ___initialize variabes that will be used through the code___
- Eigen::VectorXs problem_origin(16);
- Eigen::Vector7s imu_pose((Eigen::Vector7s()<<0,0,0,0,0,0,1).finished()), odom_pose((Eigen::Vector7s()<<0,0,0,0,0,0,1).finished());
- problem_origin << 0,0,0, 0,0,0,1, 0,0,0, 0,0,0, 0,0,0;
-
- //Create vectors to store data and time
- Eigen::Vector6s data_imu, data_odom;
- Scalar clock;
- TimeStamp ts(0), ts_output(0); //will be used to store the data timestamps and set timestamps in captures
-
- // ___Define expected values___
- Eigen::Vector7s expected_KF1_pose((Eigen::Vector7s()<<0,0,0,0,0,0,1).finished()), expected_KF2_pose((Eigen::Vector7s()<<0,-0.06,0,0,0,0,11).finished());
-
- //#################################################### SETTING PROBLEM
- std::string wolf_root = _WOLF_ROOT_DIR;
-
- // ___Create the WOLF Problem + define origin of the problem___
- ProblemPtr problem = Problem::create("PQVBB 3D");
- CeresManager* ceres_manager = new CeresManager(problem);
-
- // ___Configure Ceres if needed___
-
- // ___Create sensors + processors___
- SensorIMUPtr sensorIMU = std::static_pointer_cast<SensorIMU>(problem->installSensor("IMU", "Main IMU", imu_pose, wolf_root + "/src/examples/sensor_imu.yaml"));
- ProcessorIMUPtr processorIMU = std::static_pointer_cast<ProcessorIMU>(problem->installProcessor("IMU", "IMU pre-integrator", "Main IMU", wolf_root + "/src/examples/processor_imu.yaml"));
-
- SensorOdom3DPtr sensorOdom = std::static_pointer_cast<SensorOdom3D>(problem->installSensor("ODOM 3D", "odom", odom_pose, wolf_root + "/src/examples/sensor_odom_3D_HQ.yaml"));
- ProcessorOdom3DPtr processorOdom = std::static_pointer_cast<ProcessorOdom3D>(problem->installProcessor("ODOM 3D", "odom", "odom", wolf_root + "/src/examples/processor_odom_3D.yaml"));
-
- // ___set origin of processors to the problem's origin___
- FrameIMUPtr KF1 = std::static_pointer_cast<FrameIMU>(processorIMU->setOrigin(problem_origin, ts)); // XXX JS: setting ts to zero, and then reading clock from data, is inconsistent.
- processorOdom->setOrigin(KF1);
-
- //#################################################### PROCESS DATA
- // ___process IMU and odometry___
-
- //Create captures
- CaptureIMUPtr imu_ptr = std::make_shared<CaptureIMU>(ts, sensorIMU, data_imu, Matrix6s::Identity(), Vector6s::Zero()); //ts is set at 0
- CaptureMotionPtr mot_ptr = std::make_shared<CaptureMotion>(ts, sensorOdom, data_odom, 7, 6, nullptr);
-
- //while we do not reach the end of file, read IMU input (ts, Ax, Ay, Az, Wx, Wy, Wz) and process data through capture
- while(!imu_data_input.eof())
- {
- //read
- imu_data_input >> clock >> data_imu[0] >> data_imu[1] >> data_imu[2] >> data_imu[3] >> data_imu[4] >> data_imu[5];
-
- //set capture
- ts.set(clock);
- imu_ptr->setTimeStamp(ts);
- imu_ptr->setData(data_imu);
-
- //process
- sensorIMU->process(imu_ptr);
- }
-
- //All IMU data have been processed, close the file
- imu_data_input.close();
-
- //A KeyFrame should have been created (depending on time_span in processors). get the last KeyFrame
- // XXX JS: in my opinion, we should control the KF creation better, not using time span. Is it possible?
- #ifdef ADD_KF3
- //Add a KeyFrame just before the motion actually starts (we did not move yet)
- data_odom << 0,0,0, 0,0,0;
- TimeStamp t_middle(0.307585);
- mot_ptr->setTimeStamp(t_middle);
- mot_ptr->setData(data_odom);
- sensorOdom->process(mot_ptr);
-
- //Also add a keyframe at the end of the motion
- data_odom << 0,-0.06,0, 0,0,0;
- ts.set(0.981573); //comment this if you want the last KF to be created at last imu's ts
- mot_ptr->setTimeStamp(ts);
- mot_ptr->setData(data_odom);
- sensorOdom->process(mot_ptr);
-
- FrameIMUPtr KF2 = std::static_pointer_cast<FrameIMU>(problem->getTrajectory()->closestKeyFrameToTimeStamp(t_middle));
- FrameIMUPtr KF3 = std::static_pointer_cast<FrameIMU>(problem->getTrajectory()->closestKeyFrameToTimeStamp(ts));
- #else
- //now impose final odometry using last timestamp of imu
- data_odom << 0,-0.06,0, 0,0,0;
- mot_ptr->setTimeStamp(ts);
- mot_ptr->setData(data_odom);
- sensorOdom->process(mot_ptr);
-
- FrameIMUPtr KF2 = std::static_pointer_cast<FrameIMU>(problem->getTrajectory()->closestKeyFrameToTimeStamp(ts));
- #endif
-
- //#################################################### OPTIMIZATION PART
- // ___Create needed factors___
-
- //Add Fix3D factor on first KeyFrame (with large covariance except for yaw)
- Eigen::MatrixXs featureFix_cov(6,6);
- featureFix_cov = Eigen::MatrixXs::Identity(6,6);
- featureFix_cov.topLeftCorner(3,3) *= 1e-8; // position variances (it's fixed anyway)
- featureFix_cov(3,3) = pow( .02 , 2); // roll variance
- featureFix_cov(4,4) = pow( .02 , 2); // pitch variance
- featureFix_cov(5,5) = pow( .01 , 2); // yaw variance
- CaptureBasePtr cap_fix = KF1->addCapture(std::make_shared<CaptureMotion>(0, nullptr, problem_origin.head(7), 7, 6, nullptr));
- FeatureBasePtr featureFix = cap_fix->addFeature(std::make_shared<FeatureBase>("ODOM 3D", problem_origin.head(7), featureFix_cov));
- FactorFix3DPtr fac_fix = std::static_pointer_cast<FactorPose3D>(featureFix->addFactor(std::make_shared<FactorPose3D>(featureFix)));
-
- Eigen::MatrixXs featureFixBias_cov(6,6);
- featureFixBias_cov = Eigen::MatrixXs::Identity(6,6);
- featureFixBias_cov.topLeftCorner(3,3) *= sensorIMU->getAbInitialStdev() * sensorIMU->getAbInitialStdev();
- featureFixBias_cov.bottomRightCorner(3,3) *= sensorIMU->getWbInitialStdev() * sensorIMU->getWbInitialStdev();
- CaptureBasePtr cap_fixbias = KF1->addCapture(std::make_shared<CaptureMotion>(0, nullptr, problem_origin.tail(6), featureFixBias_cov, 6, 6, nullptr));
- //create a FeatureBase to factor biases
- FeatureBasePtr featureFixBias = cap_fixbias->addFeature(std::make_shared<FeatureBase>("FIX BIAS", problem_origin.tail(6), featureFixBias_cov));
- FactorFixBiasPtr fac_fixBias = std::static_pointer_cast<FactorFixBias>(featureFixBias->addFactor(std::make_shared<FactorFixBias>(featureFixBias)));
-
- // ___Fix/Unfix stateblocks___
- KF1->getP()->fix();
- KF1->getO()->unfix();
- KF1->getV()->fix();
- KF1->getAccBias()->unfix();
- KF1->getGyroBias()->unfix();
-
- #ifdef ADD_KF3
- KF2->getP()->fix();
- KF2->getO()->unfix();
- KF2->getV()->fix();
- KF2->getAccBias()->unfix();
- KF2->getGyroBias()->unfix();
-
- KF3->getP()->unfix();
- KF3->getO()->unfix();
- KF3->getV()->fix();
- KF3->getAccBias()->unfix();
- KF3->getGyroBias()->unfix();
- #else
- KF2->getP()->unfix();
- KF2->getO()->unfix();
- KF2->getV()->fix();
- KF2->getAccBias()->unfix();
- KF2->getGyroBias()->unfix();
- #endif
-
- #ifdef OUTPUT_RESULTS
- // ___OUTPUT___
- /* Produce output file for matlab visualization
- * first output : estimated trajectory BEFORE optimization (getting the states each millisecond)
- */
-
- unsigned int time_iter(0);
- Scalar ms(0.001);
- ts_output.set(0);
- while(ts_output.get() < ts.get() + ms)
- {
- output_results_before << ts_output.get() << "\t" << problem->getState(ts_output).transpose() << std::endl;
- time_iter++;
- ts_output.set(time_iter * ms);
- }
- #endif
-
- // ___Solve + compute covariances___
- problem->print(4,0,1,0);
- std::string report = ceres_manager->solve(SolverManager::ReportVerbosity::BRIEF); // 0: nothing, 1: BriefReport, 2: FullReport
- ceres_manager->computeCovariances(SolverManager::CovarianceBlocksToBeComputed::ALL_MARGINALS);
- problem->print(1,0,1,0);
-
- //#################################################### RESULTS PART
-
- // ___Get standard deviation from covariances___
- #ifdef ADD_KF3
- Eigen::MatrixXs cov_KF1(16,16), cov_KF2(16,16), cov_KF3(16,16);
-
- problem->getFrameCovariance(KF1, cov_KF1);
- problem->getFrameCovariance(KF2, cov_KF2);
- problem->getFrameCovariance(KF3, cov_KF3);
-
- Eigen::Matrix<wolf::Scalar, 16, 1> stdev_KF1, stdev_KF2, stdev_KF3;
-
- stdev_KF1 = cov_KF1.diagonal().array().sqrt();
- stdev_KF2 = cov_KF2.diagonal().array().sqrt();
- stdev_KF3 = cov_KF3.diagonal().array().sqrt();
-
- WOLF_DEBUG("stdev KF1 : ", stdev_KF1.transpose());
- WOLF_DEBUG("stdev KF2 : ", stdev_KF2.transpose());
- WOLF_DEBUG("stdev KF3 : ", stdev_KF3.transpose());
- #else
- Eigen::MatrixXs cov_KF1(16,16), cov_KF2(16,16);
-
- problem->getFrameCovariance(KF1, cov_KF1);
- problem->getFrameCovariance(KF2, cov_KF2);
-
- Eigen::Matrix<wolf::Scalar, 16, 1> stdev_KF1, stdev_KF2;
-
- stdev_KF1 = cov_KF1.diagonal().array().sqrt();
- stdev_KF2 = cov_KF2.diagonal().array().sqrt();
-
- WOLF_DEBUG("stdev KF1 : \n", stdev_KF1.transpose());
- WOLF_DEBUG("stdev KF2 : \n", stdev_KF2.transpose());
- #endif
-
-
- #ifdef OUTPUT_RESULTS
- // ___OUTPUT___
- /* Produce output file for matlab visualization
- * Second output: KF2 position standard deviation computed
- * estimated trajectory AFTER optimization
- * + get KF2 timestamp + state just in case the loop is not working as expected
- */
-
- //estimated trajectort
- time_iter = 0;
- ts_output.set(0);
- while(ts_output.get() < ts.get() + ms)
- {
- output_results_after << ts_output.get() << "\t" << problem->getState(ts_output).transpose() << std::endl;
- time_iter++;
- ts_output.set(time_iter * ms);
- }
-
- //finally, output the timestamp, state and stdev associated to KFs
- #ifdef ADD_KF3
- checking << KF2->getTimeStamp().get() << "\t" << KF2->getState().transpose() << "\t" << stdev_KF2.transpose() << std::endl;
- checking << KF3->getTimeStamp().get() << "\t" << KF3->getState().transpose() << "\t" << stdev_KF3.transpose() << std::endl;
- #else
- checking << KF2->getTimeStamp().get() << "\t" << KF2->getState().transpose() << "\t" << stdev_KF2.transpose() << std::endl;
- #endif
- #endif
-
- // ___Are expected values in the range of estimated +/- 2*stdev ?___
-
- #ifdef OUTPUT_RESULTS
- output_results_before.close();
- output_results_after.close();
- checking.close();
- #endif
-
- return 0;
-}
diff --git a/demos/demo_imuDock_autoKFs.cpp b/demos/demo_imuDock_autoKFs.cpp
deleted file mode 100644
index 43a54d654..000000000
--- a/demos/demo_imuDock_autoKFs.cpp
+++ /dev/null
@@ -1,311 +0,0 @@
-/**
- * \file test_imuDock_autoKFs.cpp
- *
- * Created on: July 22, 2017
- * \author: Dinesh Atchuthan
- */
-
-#include "base/processor/processor_IMU.h"
-#include "base/sensor/sensor_IMU.h"
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-#include "base/sensor/sensor_odom_3D.h"
-#include "base/processor/processor_odom_3D.h"
-
-//Factors headers
-#include "base/factor/factor_fix_bias.h"
-
-//std
-#include <iostream>
-#include <fstream>
-#include "base/factor/factor_pose_3D.h"
-
-#define OUTPUT_RESULTS
-//#define AUTO_KFS
-
-/* OFFLINE VERSION
- In this test, we use the experimental conditions needed for Humanoids 2017.
- IMU data are acquired using the docking station.
-
- Factors are (supposing to KeyFrames, stateblocks or first Keyframe are noted *1 and second Keyframes's are *2) :
- invar : P1, V1, V2
- var : Q1,B1,P2,Q2,B2
-
- All Keyframes coming after KF2 are constrained just like KF2
- factors : Odometry factor between KeyFrames
- IMU factor
- FixBias factor --> makes the problem observable (adding a big covariance on all part but a smaller one on yaw)
- Fix3D factor
-
- What we expect : Estimate biases (this will strongly depend on the actual trajectory of the IMU)
- Estimate the position and orienttion of the IMU (check with the standard deviation using covariance matrix)
-
- Representation of the application:
-
- Imu
- KF1----------â—¼----------KF2--..
- /----P1----------\ /----------P2--.. invar : P1, V1, V2
- Abs|------â—¼ â—¼ var : Q1,B1,P2,Q2,B2
- \----Q1----------/ \----------Q2--..
- V1 Odom v2 ..
- Abs|------â—¼-----B1 B2 ..
-*/
-int main(int argc, char** argv)
-{
- //#################################################### INITIALIZATION
- using namespace wolf;
-
- //___get input files for imu and odom data___
- std::ifstream imu_data_input, odom_data_input;
- const char * filename_imu;
- const char * filename_odom;
- if (argc < 03)
- {
- WOLF_ERROR("Missing input argument : path to imu or/and odom data file(s).")
- return 1; //return with error
- }
- else
- {
- filename_imu = argv[1];
- filename_odom = argv[2];
-
- imu_data_input.open(filename_imu);
- WOLF_INFO("imu file : ", filename_imu)
- odom_data_input.open(filename_odom);
- WOLF_INFO("odom file : ", filename_odom)
- }
-
- // ___Check if the file is correctly opened___
- if(!imu_data_input.is_open() || !odom_data_input.is_open()){
- WOLF_ERROR("Failed to open data file ! Exiting")
- return 1;
- }
-
- #ifdef OUTPUT_RESULTS
- //define output file
- std::ofstream output_results_before, output_results_after, checking;
- output_results_before.open("imu_dock_beforeOptim.dat");
- output_results_after.open("imu_dock_afterOptim.dat");
- checking.open("KF_pose_stdev.dat");
- #endif
-
- // ___initialize variabes that will be used through the code___
- Eigen::VectorXs problem_origin(16);
- Eigen::Vector7s imu_pose((Eigen::Vector7s()<<0,0,0,0,0,0,1).finished()), odom_pose((Eigen::Vector7s()<<0,0,0,0,0,0,1).finished());
- problem_origin << 0,0,0, 0,0,0,1, 0,0,0, 0,0,0, 0,0,0;
-
- //Create vectors to store data and time
- Eigen::Vector6s data_imu, data_odom;
- Scalar clock;
- TimeStamp ts(0), ts_output(0); //will be used to store the data timestamps and set timestamps in captures
-
- // ___Define expected values___
- Eigen::Vector7s expected_KF1_pose((Eigen::Vector7s()<<0,0,0,0,0,0,1).finished()), expected_KF2_pose((Eigen::Vector7s()<<0,-0.06,0,0,0,0,11).finished());
-
- #ifdef AUTO_KFs
- std::array<Scalar, 50> lastms_imuData;
- #endif
- //#################################################### SETTING PROBLEM
- std::string wolf_root = _WOLF_ROOT_DIR;
-
- // ___Create the WOLF Problem + define origin of the problem___
- ProblemPtr problem = Problem::create("PQVBB 3D");
- CeresManager* ceres_manager = new CeresManager(problem);
-
- // ___Configure Ceres if needed___
-
- // ___Create sensors + processors___
- SensorIMUPtr sensorIMU = std::static_pointer_cast<SensorIMU>(problem->installSensor("IMU", "Main IMU", imu_pose, wolf_root + "/src/examples/sensor_imu.yaml"));
- ProcessorIMUPtr processorIMU = std::static_pointer_cast<ProcessorIMU>(problem->installProcessor("IMU", "IMU pre-integrator", "Main IMU", wolf_root + "/src/examples/processor_imu.yaml"));
-
- SensorOdom3DPtr sensorOdom = std::static_pointer_cast<SensorOdom3D>(problem->installSensor("ODOM 3D", "odom", odom_pose, wolf_root + "/src/examples/sensor_odom_3D_HQ.yaml"));
- ProcessorOdom3DPtr processorOdom = std::static_pointer_cast<ProcessorOdom3D>(problem->installProcessor("ODOM 3D", "odom", "odom", wolf_root + "/src/examples/processor_odom_3D.yaml"));
-
- // ___set origin of processors to the problem's origin___
- FrameIMUPtr KF1 = std::static_pointer_cast<FrameIMU>(processorIMU->setOrigin(problem_origin, ts)); // XXX JS: setting ts to zero, and then reading clock from data, is inconsistent.
- processorOdom->setOrigin(KF1);
-
- //#################################################### PROCESS DATA
- // ___process IMU and odometry___
-
- //Create captures
- CaptureIMUPtr imu_ptr = std::make_shared<CaptureIMU>(ts, sensorIMU, data_imu, Matrix6s::Identity(), Vector6s::Zero()); //ts is set at 0
- CaptureMotionPtr mot_ptr = std::make_shared<CaptureMotion>(ts, sensorOdom, data_odom, 7, 6, nullptr);
-
- //while we do not reach the end of file, read IMU input (ts, Ax, Ay, Az, Wx, Wy, Wz) and process data through capture
- while(!imu_data_input.eof())
- {
- //read
- imu_data_input >> clock >> data_imu[0] >> data_imu[1] >> data_imu[2] >> data_imu[3] >> data_imu[4] >> data_imu[5];
-
- //set capture
- ts.set(clock);
- imu_ptr->setTimeStamp(ts);
- imu_ptr->setData(data_imu);
-
- //process
- sensorIMU->process(imu_ptr);
- }
-
- //Process all the odom data
- // XXX JS: in my opinion, we should control the KF creation better, not using time span. Is it possible?
- while(!odom_data_input.eof())
- {
- //read
- odom_data_input >> clock >> data_odom[0] >> data_odom[1] >> data_odom[2] >> data_odom[3] >> data_odom[4] >> data_odom[5];
-
- //set capture
- ts.set(clock);
- mot_ptr->setTimeStamp(ts);
- mot_ptr->setData(data_odom);
-
- #ifdef AUTO_KFS
- /* We want the KFs to be generated automatically but not using time span as argument of this generation
- * For our application, w want the KFs to be generated when an odometry data is given under condition that the IMU is not moving
- * We check wether the IMU is moving or not by computing the current stdev of the IMU based on data received during 50ms before the odom timestamp
- * We compare this value to the stdev (noise) of the sensor (see sensor_imu.yaml)
- * If the current stdev is below a threshold then we process the odometry data !
- */
-
- // TODO : get data to compute stdev with directly from the capture
- // -> see how these data are stored and change getIMUStdev(..) function defined below main() in this file
- // -> then just use the function to get this stdev of corresponding data
-
- #else
- //process anyway. KFs will be generated based on the configuration given in processor_odom_3D.yaml
- sensorOdom->process(mot_ptr);
- #endif
- }
-
- //All data have been processed, close the files
- imu_data_input.close();
- odom_data_input.close();
-
- //A KeyFrame should have been created (depending on time_span in processors). get all frames
- FrameBasePtrList trajectory = problem->getTrajectory()->getFrameList();
-
-
- //#################################################### OPTIMIZATION PART
- // ___Create needed factors___
-
- //Add Fix3D factor on first KeyFrame (with large covariance except for yaw)
- Eigen::MatrixXs featureFix_cov(6,6);
- featureFix_cov = Eigen::MatrixXs::Identity(6,6);
- featureFix_cov.topLeftCorner(3,3) *= 1e-8; // position variances (it's fixed anyway)
- featureFix_cov(3,3) = pow( .01 , 2); // roll variance
- featureFix_cov(4,4) = pow( .01 , 2); // pitch variance
- featureFix_cov(5,5) = pow( .001 , 2); // yaw variance
- CaptureBasePtr cap_fix = KF1->addCapture(std::make_shared<CaptureMotion>(0, nullptr, problem_origin.head(7), 7, 6, nullptr));
- FeatureBasePtr featureFix = cap_fix->addFeature(std::make_shared<FeatureBase>("ODOM 3D", problem_origin.head(7), featureFix_cov));
- FactorFix3DPtr fac_fix = std::static_pointer_cast<FactorPose3D>(featureFix->addFactor(std::make_shared<FactorPose3D>(featureFix)));
-
- Eigen::MatrixXs featureFixBias_cov(6,6);
- featureFixBias_cov = Eigen::MatrixXs::Identity(6,6);
- featureFixBias_cov.topLeftCorner(3,3) *= sensorIMU->getAbInitialStdev() * sensorIMU->getAbInitialStdev();
- featureFixBias_cov.bottomRightCorner(3,3) *= sensorIMU->getWbInitialStdev() * sensorIMU->getWbInitialStdev();
- CaptureBasePtr cap_fixbias = KF1->addCapture(std::make_shared<CaptureMotion>(0, nullptr, problem_origin.tail(6), featureFixBias_cov, 6, 6, nullptr));
- //create a FeatureBase to factor biases
- FeatureBasePtr featureFixBias = cap_fixbias->addFeature(std::make_shared<FeatureBase>("FIX BIAS", problem_origin.tail(6), featureFixBias_cov));
- FactorFixBiasPtr fac_fixBias = std::static_pointer_cast<FactorFixBias>(featureFixBias->addFactor(std::make_shared<FactorFixBias>(featureFixBias)));
-
- // ___Fix/Unfix stateblocks___
- // fix all Keyframes here
-
- FrameIMUPtr frame_imu;
- for(auto frame : trajectory)
- {
- frame_imu = std::static_pointer_cast<FrameIMU>(frame);
- if(frame_imu->isKey())
- {
- frame_imu->getP()->fix();
- frame_imu->getO()->unfix();
- frame_imu->getV()->setState((Eigen::Vector3s()<<0,0,0).finished()); //fix all velocties to 0 ()
- frame_imu->getV()->fix();
- frame_imu->getAccBias()->unfix();
- frame_imu->getGyroBias()->unfix();
- }
- }
-
- //KF1 (origin) needs to be also fixed in position
- KF1->getP()->fix();
-
- #ifdef OUTPUT_RESULTS
- // ___OUTPUT___
- /* Produce output file for matlab visualization
- * first output : estimated trajectory BEFORE optimization (getting the states each millisecond)
- */
-
- unsigned int time_iter(0);
- Scalar ms(0.001);
- ts_output.set(0);
- while(ts_output.get() < ts.get() + ms)
- {
- output_results_before << ts_output.get() << "\t" << problem->getState(ts_output).transpose() << std::endl;
- time_iter++;
- ts_output.set(time_iter * ms);
- }
- #endif
-
- // ___Solve + compute covariances___
- problem->print(4,0,1,0);
- std::string report = ceres_manager->solve(SolverManager::ReportVerbosity::BRIEF);
- ceres_manager->computeCovariances(SolverManager::CovarianceBlocksToBeComputed::ALL_MARGINALS);
- problem->print(1,0,1,0);
-
- //#################################################### RESULTS PART
-
- // ___Get standard deviation from covariances___ and output this in a file
- Eigen::MatrixXs cov_KF(16,16);
- Eigen::Matrix<wolf::Scalar, 16, 1> stdev_KF;
- for(auto frame : trajectory)
- {
- if(frame->isKey())
- {
- problem->getFrameCovariance(frame, cov_KF);
- stdev_KF = cov_KF.diagonal().array().sqrt();
- #ifdef OUTPUT_RESULTS
- checking << frame->getTimeStamp().get() << "\t" << frame->getState().transpose() << "\t" << stdev_KF.transpose() << std::endl;
- #endif
- }
- }
-
- #ifdef OUTPUT_RESULTS
- // ___OUTPUT___
- /* Produce output file for matlab visualization
- * Second output: KF position standard deviation computed
- * estimated trajectory AFTER optimization
- */
-
- //estimated trajectort
- time_iter = 0;
- ts_output.set(0);
- while(ts_output.get() < ts.get() + ms)
- {
- output_results_after << ts_output.get() << "\t" << problem->getState(ts_output).transpose() << std::endl;
- time_iter++;
- ts_output.set(time_iter * ms);
- }
-
- //Finished writing in files : close them
- output_results_before.close();
- output_results_after.close();
- checking.close();
- #endif
-
- return 0;
-}
-
-/*Scalar getIMUStdev(Eigen::VectorXs _data) //input argument : whatever will contain the data in the capture
-{
- Eigen::Vector6s mean(Eigen::Vector6s::Zero()), stdev(Eigen::Vector6s::Zero());
- unsigned int _data_size(_data.size());
-
- mean = _data.mean()/_data_size;
-
- for (unsigned int i = 0; i < _data_size; i++)
- {
- stdev += pow(_data()-mean,2); //get the correct data from the container
- }
- return (stdev.array().sqrt()).maxCoeff();
-}*/
diff --git a/demos/demo_imuPlateform_Offline.cpp b/demos/demo_imuPlateform_Offline.cpp
deleted file mode 100644
index 4b923de89..000000000
--- a/demos/demo_imuPlateform_Offline.cpp
+++ /dev/null
@@ -1,266 +0,0 @@
-//Wolf
-#include "base/capture/capture_IMU.h"
-#include "base/processor/processor_IMU.h"
-#include "base/sensor/sensor_IMU.h"
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/sensor/sensor_odom_3D.h"
-#include "base/factor/factor_odom_3D.h"
-#include "base/state_block/state_block.h"
-#include "base/state_block/state_quaternion.h"
-#include "base/processor/processor_odom_3D.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-
-//std
-#include <iostream>
-#include <fstream>
-#include <iomanip>
-#include <ctime>
-#include <cmath>
-
-#define DEBUG_RESULTS
-
-int _kbhit();
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
- using std::shared_ptr;
- using std::make_shared;
- using std::static_pointer_cast;
-
- // LOADING DATA FILE (IMU)
- // FOR IMU, file content is : Timestampt\t Ax\t Ay\t Az\t Wx\t Wy\t Wz
-
- std::ifstream imu_data_input;
- const char * filename_imu;
- if (argc < 02)
- {
-
- WOLF_ERROR("Missing input argument! : needs 1 argument (path to imu data file).")
- return 1;
- }
- else
- {
- filename_imu = argv[1];
-
- imu_data_input.open(filename_imu);
- WOLF_INFO("imu file : ", filename_imu)
-
- //std::string dummy; //this is needed only if first line is headers or useless data
- //getline(imu_data_input, dummy);
- }
-
- if(!imu_data_input.is_open()){
- std::cerr << "Failed to open data files... Exiting" << std::endl;
- return 1;
- }
-
- #ifdef DEBUG_RESULTS
- std::ofstream debug_results;
- debug_results.open("debug_results_imu_constrained0.dat");
- if(debug_results)
- debug_results << "%%TimeStamp\t"
- << "X_x\t" << "X_y\t" << "X_z\t" << "Xq_x\t" << "Xq_y\t" << "Xq_z\t" << "Xq_w\t" << "Xv_x\t" << "Xv_y\t" << "Xv_z\t"
- << "Cov_X\t" << "Cov_Y\t" << "Cov_Z\t" << "Cov_Qx\t" << "Cov_Qy\t" << "Cov_Qz\t" << "Cov_Qw" << "Cov_Vx\t" << "Cov_Vy\t" << "Cov_Vz\t" << std::endl;
- #endif
-
- //===================================================== SETTING PROBLEM
- std::string wolf_root = _WOLF_ROOT_DIR;
-
- // WOLF PROBLEM
- ProblemPtr wolf_problem_ptr_ = Problem::create("PQVBB 3D");
- Eigen::VectorXs x_origin(16);
- x_origin << 0,0,0, 0,0,0,1, 0,0,0, 0,0,0, 0,0,0; //INITIAL CONDITIONS
- TimeStamp t(0);
-
- // CERES WRAPPER
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;ceres::LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- ceres_options.max_num_iterations = 1e4;
- CeresManager* ceres_manager_wolf_diff = new CeresManager(wolf_problem_ptr_, ceres_options);
-
- // SENSOR + PROCESSOR IMU
- SensorBasePtr sen0_ptr = wolf_problem_ptr_->installSensor("IMU", "Main IMU", (Vector7s()<<0,0,0,0,0,0,1).finished(), wolf_root + "/src/examples/sensor_imu.yaml");
- ProcessorIMUParamsPtr prc_imu_params = std::make_shared<ProcessorParamsIMU>();
- prc_imu_params->max_time_span = 10;
- prc_imu_params->max_buff_length = 1000000000; //make it very high so that this condition will not pass
- prc_imu_params->dist_traveled = 1000000000;
- prc_imu_params->angle_turned = 1000000000;
-
- ProcessorBasePtr processor_ptr_ = wolf_problem_ptr_->installProcessor("IMU", "IMU pre-integrator", sen0_ptr, prc_imu_params);
- SensorIMUPtr sen_imu = std::static_pointer_cast<SensorIMU>(sen0_ptr);
- ProcessorIMUPtr processor_ptr_imu = std::static_pointer_cast<ProcessorIMU>(processor_ptr_);
-
- // SENSOR + PROCESSOR ODOM 3D
- SensorBasePtr sen1_ptr = wolf_problem_ptr_->installSensor("ODOM 3D", "odom", (Vector7s()<<0,0,0,0,0,0,1).finished(), wolf_root + "/src/examples/sensor_odom_3D.yaml");
- ProcessorParamsOdom3DPtr prc_odom3D_params = std::make_shared<ProcessorParamsOdom3D>();
- prc_odom3D_params->max_time_span = 1.9999;
- prc_odom3D_params->max_buff_length = 1000000000; //make it very high so that this condition will not pass
- prc_odom3D_params->dist_traveled = 1000000000;
- prc_odom3D_params->angle_turned = 1000000000;
-
- ProcessorBasePtr processor_ptr_odom = wolf_problem_ptr_->installProcessor("ODOM 3D", "odom", sen1_ptr, prc_odom3D_params);
- SensorOdom3DPtr sen_odom3D = std::static_pointer_cast<SensorOdom3D>(sen1_ptr);
- ProcessorOdom3DPtr processor_ptr_odom3D = std::static_pointer_cast<ProcessorOdom3D>(processor_ptr_odom);
-
- // reset origin of problem
- t.set(0);
-
- FrameIMUPtr origin_KF = std::static_pointer_cast<FrameIMU>(processor_ptr_imu->setOrigin(x_origin, t));
- processor_ptr_odom3D->setOrigin(origin_KF);
-
- //fix parts of the problem if needed
- origin_KF->getP()->fix();
- origin_KF->getO()->fix();
- //===================================================== PROCESS DATA
- // PROCESS DATA
-
- Eigen::Vector6s data_imu, data_odom3D;
- data_imu << 0,0,-wolf::gravity()(2), 0,0,0;
- data_odom3D << 0,-0.06,0, 0,0,0;
-
- Scalar input_clock;
- TimeStamp ts(0);
- wolf::CaptureIMUPtr imu_ptr = std::make_shared<CaptureIMU>(ts, sen_imu, data_imu, Matrix6s::Identity(), Vector6s::Zero());
- wolf::CaptureMotionPtr mot_ptr = std::make_shared<CaptureMotion>(t, sen_odom3D, data_odom3D, 6, 6, nullptr);
-
- //when we find a IMU timestamp corresponding with this odometry timestamp then we process odometry measurement
- t = ts;
-
- clock_t begin = clock();
-
- while( !imu_data_input.eof())
- {
- // PROCESS IMU DATA
- // Time and data variables
- imu_data_input >> input_clock >> data_imu[0] >> data_imu[1] >> data_imu[2] >> data_imu[3] >> data_imu[4] >> data_imu[5]; //Ax, Ay, Az, Gx, Gy, Gz
-
- ts.set(input_clock);
- imu_ptr->setTimeStamp(ts);
- imu_ptr->setData(data_imu);
-
- // process data in capture
- imu_ptr->getTimeStamp();
- sen_imu->process(imu_ptr);
- }
-
- TimeStamp t0, tf;
- t0 = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().front().ts_;
- tf = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
- int N = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().size();
-
- //Finally, process the only one odom input
- mot_ptr->setTimeStamp(ts);
- mot_ptr->setData(data_odom3D);
- sen_odom3D->process(mot_ptr);
-
- clock_t end = clock();
- FrameIMUPtr last_KF = std::static_pointer_cast<FrameIMU>(wolf_problem_ptr_->getTrajectory()->closestKeyFrameToTimeStamp(ts));
-
- //closing file
- imu_data_input.close();
- //===================================================== END{PROCESS DATA}
-
- double elapsed_secs = double(end - begin) / CLOCKS_PER_SEC;
-
- // Final state
- std::cout << "\nIntegration results ----------------------------------------------------------------------------------------------" << std::endl;
- std::cout << "Initial state: " << std::fixed << std::setprecision(3) << std::setw(8)
- << x_origin.head(16).transpose() << std::endl;
- std::cout << "Integrated delta: " << std::fixed << std::setprecision(3) << std::setw(8)
- << wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_.transpose() << std::endl;
- std::cout << "Integrated state: " << std::fixed << std::setprecision(3) << std::setw(8)
- << wolf_problem_ptr_->getProcessorMotion()->getCurrentState().head(16).transpose() << std::endl;
- std::cout << "Integrated std : " << std::fixed << std::setprecision(3) << std::setw(8)
- << (wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_cov_.diagonal().transpose()).array().sqrt() << std::endl;
-
- // Print statistics
- std::cout << "\nStatistics -----------------------------------------------------------------------------------" << std::endl;
- std::cout << "If you want meaningful CPU metrics, remove all couts in the loop / remove DEBUG_RESULTS definition variable, and compile in RELEASE mode!" << std::endl;
-
- /*TimeStamp t0, tf;
- t0 = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().front().ts_;
- tf = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
- int N = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().size();*/
- std::cout << "t0 : " << t0.get() << " s" << std::endl;
- std::cout << "tf : " << tf.get() << " s" << std::endl;
- std::cout << "duration : " << tf-t0 << " s" << std::endl;
- std::cout << "N samples : " << N << std::endl;
- std::cout << "frequency : " << (N-1)/(tf-t0) << " Hz" << std::endl;
- std::cout << "CPU time : " << elapsed_secs << " s" << std::endl;
- std::cout << "s/integr : " << elapsed_secs/(N-1)*1e6 << " us" << std::endl;
- std::cout << "integr/s : " << (N-1)/elapsed_secs << " ips" << std::endl;
-
- //fix parts of the problem if needed
- origin_KF->getP()->fix();
- origin_KF->getO()->fix();
- origin_KF->getV()->fix();
-
- std::cout << "\t\t\t ______solving______" << std::endl;
- std::string report = ceres_manager_wolf_diff->solve(SolverManager::ReportVerbosity::FULL);// 0: nothing, 1: BriefReport, 2: FullReport
- std::cout << report << std::endl;
- ceres_manager_wolf_diff->computeCovariances(SolverManager::CovarianceBlocksToBeComputed::ALL);
- std::cout << "\t\t\t ______solved______" << std::endl;
-
- wolf_problem_ptr_->print(4,1,1,1);
-
- #ifdef DEBUG_RESULTS
- Eigen::VectorXs frm_state(16);
- Eigen::Matrix<wolf::Scalar, 16, 1> cov_stdev;
- Eigen::MatrixXs covX(16,16);
- Eigen::MatrixXs cov3(Eigen::Matrix3s::Zero());
-
- wolf::FrameBasePtrList frame_list = wolf_problem_ptr_->getTrajectory()->getFrameList();
- for(FrameBasePtr frm_ptr : frame_list)
- {
- if(frm_ptr->isKey())
- {
- //prepare needed variables
- FrameIMUPtr frmIMU_ptr = std::static_pointer_cast<FrameIMU>(frm_ptr);
- frm_state = frmIMU_ptr->getState();
- ts = frmIMU_ptr->getTimeStamp();
-
- //get data from covariance blocks
- wolf_problem_ptr_->getFrameCovariance(frmIMU_ptr, covX);
- wolf_problem_ptr_->getCovarianceBlock(frmIMU_ptr->getV(), frmIMU_ptr->getV(), cov3);
- covX.block(7,7,3,3) = cov3;
- wolf_problem_ptr_->getCovarianceBlock(frmIMU_ptr->getAccBias(), frmIMU_ptr->getAccBias(), cov3);
- covX.block(10,10,3,3) = cov3;
- wolf_problem_ptr_->getCovarianceBlock(frmIMU_ptr->getGyroBias(), frmIMU_ptr->getGyroBias(), cov3);
- covX.block(13,13,3,3) = cov3;
- for(int i = 0; i<16; i++)
- cov_stdev(i) = ( covX(i,i)? 2*sqrt(covX(i,i)):0); //if diagonal value is 0 then store 0 else store 2*sqrt(diag_value)
-
- debug_results << std::setprecision(16) << ts.get() << "\t" << frm_state(0) << "\t" << frm_state(1) << "\t" << frm_state(2)
- << "\t" << frm_state(3) << "\t" << frm_state(4) << "\t" << frm_state(5) << "\t" << frm_state(6)
- << "\t" << frm_state(7) << "\t" << frm_state(8) << "\t" << frm_state(9)
- << "\t" << frm_state(10) << "\t" << frm_state(11) << "\t" << frm_state(12) << "\t" << frm_state(13) << "\t" << frm_state(14) << "\t" << frm_state(15)
- << "\t" << cov_stdev(0) << "\t" << cov_stdev(1) << "\t" << cov_stdev(2)
- << "\t" << cov_stdev(3) << "\t" << cov_stdev(4) << "\t" << cov_stdev(5) << "\t" << cov_stdev(6)
- << "\t" << cov_stdev(7) << "\t" << cov_stdev(8) << "\t" << cov_stdev(9)
- << "\t" << cov_stdev(10) << "\t" << cov_stdev(11) << "\t" << cov_stdev(12) << "\t" << cov_stdev(13) << "\t" << cov_stdev(14) << "\t" << cov_stdev(15) << std::endl;
- }
- }
-
- debug_results.close();
- WOLF_WARN("WARNING : DEBUG_RESULTS ACTIVATED - slows the process (writing results to result_debugs.dat file)")
-
- #endif
-
- return 0;
-
-}
-
-int _kbhit()
-{
- struct timeval tv;
- fd_set fds;
- tv.tv_sec = 0;
- tv.tv_usec = 0;
- FD_ZERO(&fds);
- FD_SET(STDIN_FILENO, &fds); //STDIN_FILENO is 0
- select(STDIN_FILENO+1, &fds, NULL, NULL, &tv);
- return FD_ISSET(STDIN_FILENO, &fds);
-}
diff --git a/demos/demo_imu_constrained0.cpp b/demos/demo_imu_constrained0.cpp
deleted file mode 100644
index e542e18e0..000000000
--- a/demos/demo_imu_constrained0.cpp
+++ /dev/null
@@ -1,374 +0,0 @@
-//Wolf
-#include "base/capture/capture_IMU.h"
-#include "base/processor/processor_IMU.h"
-#include "base/sensor/sensor_IMU.h"
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/sensor/sensor_odom_3D.h"
-#include "base/factor/factor_odom_3D.h"
-#include "base/state_block/state_block.h"
-#include "base/state_block/state_quaternion.h"
-#include "base/processor/processor_odom_3D.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-
-//std
-#include <iostream>
-#include <fstream>
-#include <iomanip>
-#include <ctime>
-#include <cmath>
-
-#define DEBUG_RESULTS
-#define KF0_EVOLUTION
-
-int _kbhit();
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
- using std::shared_ptr;
- using std::make_shared;
- using std::static_pointer_cast;
-
- // LOADING DATA FILES (IMU + ODOM)
- // FOR IMU, file content is : Timestampt\t Ax\t Ay\t Az\t Wx\t Wy\t Wz
- // FOR ODOM, file content is : Timestampt\t Δpx\t Δpy\t Δpz\t Δox\t Δoy\t Δoz
-
- std::ifstream imu_data_input;
- std::ifstream odom_data_input;
- const char * filename_imu;
- const char * filename_odom;
- if (argc < 3)
- {
- std::cout << "Missing input argument! : needs 2 argument (path to imu and odom data files)." << std::endl;
- return 1;
- }
- else
- {
- filename_imu = argv[1];
- filename_odom = argv[2];
-
- imu_data_input.open(filename_imu);
- odom_data_input.open(filename_odom);
-
- std::cout << "file imu : " << filename_imu <<"\t file odom : " << filename_odom << std::endl;
-
- //std::string dummy; //this is needed only if first line is headers or useless data
- //getline(imu_data_input, dummy);
- }
-
- if(!imu_data_input.is_open() || !odom_data_input.is_open()){
- std::cerr << "Failed to open data files... Exiting" << std::endl;
- return 1;
- }
-
- #ifdef DEBUG_RESULTS
- std::ofstream debug_results;
- debug_results.open("debug_results_imu_constrained0.dat");
- if(debug_results)
- debug_results << "%%TimeStamp\t"
- << "X_x\t" << "X_y\t" << "X_z\t" << "Xq_x\t" << "Xq_y\t" << "Xq_z\t" << "Xq_w\t" << "Xv_x\t" << "Xv_y\t" << "Xv_z\t"
- << "Cov_X\t" << "Cov_Y\t" << "Cov_Z\t" << "Cov_Qx\t" << "Cov_Qy\t" << "Cov_Qz\t" << "Cov_Qw" << "Cov_Vx\t" << "Cov_Vy\t" << "Cov_Vz\t" << std::endl;
- #endif
-
- #ifdef KF0_EVOLUTION
- std::ofstream KF0_evolution;
- KF0_evolution.open("KF0_evolution.dat");
- if(KF0_evolution)
- KF0_evolution << "%%TimeStamp\t"
- << "X_x\t" << "X_y\t" << "X_z\t" << "Xq_x\t" << "Xq_y\t" << "Xq_z\t" << "Xq_w\t" << "Xv_x\t" << "Xv_y\t" << "Xv_z\t"
- << "Cov_X\t" << "Cov_Y\t" << "Cov_Z\t" << "Cov_Qx\t" << "Cov_Qy\t" << "Cov_Qz\t" << "Cov_Qw" << "Cov_Vx\t" << "Cov_Vy\t" << "Cov_Vz\t" << std::endl;
- #endif
-
- //===================================================== SETTING PROBLEM
- std::string wolf_root = _WOLF_ROOT_DIR;
-
- // WOLF PROBLEM
- ProblemPtr wolf_problem_ptr_ = Problem::create("PQVBB 3D");
- Eigen::VectorXs x_origin(16);
- Eigen::Vector6s origin_bias;
- x_origin << 0,0,0, 0,0,0,1, 0,0,0, 0,0,0, 0,0,0; //INITIAL CONDITIONS 0.05,0.03,.00, 0.2,-0.05,.00;
- TimeStamp t(0);
-
- // initial conditions defined from data file
- // remember that matlab's quaternion is W,X,Y,Z and the one in Eigen has X,Y,Z,W form
- imu_data_input >> x_origin[0] >> x_origin[1] >> x_origin[2] >> x_origin[6] >> x_origin[3] >> x_origin[4] >> x_origin[5] >> x_origin[7] >> x_origin[8] >> x_origin[9];
- imu_data_input >> origin_bias[0] >> origin_bias[1] >> origin_bias[2] >> origin_bias[3] >> origin_bias[4] >> origin_bias[5];
-
- // CERES WRAPPER
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;ceres::LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- ceres_options.max_num_iterations = 1e4;
- CeresManager* ceres_manager_wolf_diff = new CeresManager(wolf_problem_ptr_, ceres_options);
-
- // SENSOR + PROCESSOR IMU
- SensorBasePtr sen0_ptr = wolf_problem_ptr_->installSensor("IMU", "Main IMU", (Vector7s()<<0,0,0,0,0,0,1).finished(), wolf_root + "/src/examples/sensor_imu.yaml");
- ProcessorIMUParamsPtr prc_imu_params = std::make_shared<ProcessorParamsIMU>();
- prc_imu_params->max_time_span = 10;
- prc_imu_params->max_buff_length = 1000000000; //make it very high so that this condition will not pass
- prc_imu_params->dist_traveled = 1000000000;
- prc_imu_params->angle_turned = 1000000000;
-
- ProcessorBasePtr processor_ptr_ = wolf_problem_ptr_->installProcessor("IMU", "IMU pre-integrator", sen0_ptr, prc_imu_params);
- SensorIMUPtr sen_imu = std::static_pointer_cast<SensorIMU>(sen0_ptr);
- ProcessorIMUPtr processor_ptr_imu = std::static_pointer_cast<ProcessorIMU>(processor_ptr_);
-
- // SENSOR + PROCESSOR ODOM 3D
- SensorBasePtr sen1_ptr = wolf_problem_ptr_->installSensor("ODOM 3D", "odom", (Vector7s()<<0,0,0,0,0,0,1).finished(), wolf_root + "/src/examples/sensor_odom_3D_HQ.yaml");
- ProcessorParamsOdom3DPtr prc_odom3D_params = std::make_shared<ProcessorParamsOdom3D>();
- prc_odom3D_params->max_time_span = 20.9999;
- prc_odom3D_params->max_buff_length = 1000000000; //make it very high so that this condition will not pass
- prc_odom3D_params->dist_traveled = 1000000000;
- prc_odom3D_params->angle_turned = 1000000000;
-
- ProcessorBasePtr processor_ptr_odom = wolf_problem_ptr_->installProcessor("ODOM 3D", "odom", sen1_ptr, prc_odom3D_params);
- SensorOdom3DPtr sen_odom3D = std::static_pointer_cast<SensorOdom3D>(sen1_ptr);
- ProcessorOdom3DPtr processor_ptr_odom3D = std::static_pointer_cast<ProcessorOdom3D>(processor_ptr_odom);
-
- // reset origin of problem
- t.set(0);
- Eigen::Matrix<wolf::Scalar, 10, 1> expected_final_state;
-
- FrameIMUPtr origin_KF = std::static_pointer_cast<FrameIMU>(processor_ptr_imu->setOrigin(x_origin, t));
- processor_ptr_odom3D->setOrigin(origin_KF);
-
- odom_data_input >> expected_final_state[0] >> expected_final_state[1] >> expected_final_state[2] >> expected_final_state[6] >> expected_final_state[3] >>
- expected_final_state[4] >> expected_final_state[5] >> expected_final_state[7] >> expected_final_state[8] >> expected_final_state[9];
-
- //fix parts of the problem if needed
- origin_KF->getP()->fix();
- origin_KF->getO()->fix();
- //===================================================== PROCESS DATA
- // PROCESS DATA
-
- Eigen::Vector6s data_imu, data_odom3D;
- data_imu << 0,0,-wolf::gravity()(2), 0,0,0;
- data_odom3D << 0,0,0, 0,0,0;
-
- Scalar input_clock;
- TimeStamp ts(0);
- TimeStamp t_odom(0);
- wolf::CaptureIMUPtr imu_ptr = std::make_shared<CaptureIMU>(ts, sen_imu, data_imu, Matrix6s::Identity(), Vector6s::Zero());
- wolf::CaptureMotionPtr mot_ptr = std::make_shared<CaptureMotion>(t, sen_odom3D, data_odom3D, 6, 6, nullptr);
-
- //read first odom data from file
- odom_data_input >> input_clock >> data_odom3D[0] >> data_odom3D[1] >> data_odom3D[2] >> data_odom3D[3] >> data_odom3D[4] >> data_odom3D[5];
- t_odom.set(input_clock);
- //when we find a IMU timestamp corresponding with this odometry timestamp then we process odometry measurement
- t = ts;
-
- clock_t begin = clock();
-
- while( !imu_data_input.eof() && !odom_data_input.eof() )
- {
- // PROCESS IMU DATA
- // Time and data variables
- imu_data_input >> input_clock >> data_imu[0] >> data_imu[1] >> data_imu[2] >> data_imu[3] >> data_imu[4] >> data_imu[5]; //Ax, Ay, Az, Gx, Gy, Gz
-
- ts.set(input_clock);
- imu_ptr->setTimeStamp(ts);
- imu_ptr->setData(data_imu);
-
- // process data in capture
- imu_ptr->getTimeStamp();
- sen_imu->process(imu_ptr);
-
- if(ts.get() == t_odom.get())
- {
- // PROCESS ODOM 3D DATA
- mot_ptr->setTimeStamp(t_odom);
- mot_ptr->setData(data_odom3D);
- sen_odom3D->process(mot_ptr);
-
- //prepare next odometry measurement if there is any
- odom_data_input >> input_clock >> data_odom3D[0] >> data_odom3D[1] >> data_odom3D[2] >> data_odom3D[3] >> data_odom3D[4] >> data_odom3D[5];
- t_odom.set(input_clock);
- }
-
- #ifdef KF0_EVOLUTION
-
- if( (ts.get() - t.get()) >= 0.05 )
- {
- t = ts;
- //std::string report = ceres_manager_wolf_diff->solve(1); //0: nothing, 1: BriefReport, 2: FullReport
-
- Eigen::VectorXs frm_state(16);
- frm_state = origin_KF->getState();
-
- KF0_evolution << std::setprecision(16) << ts.get() << "\t" << frm_state(0) << "\t" << frm_state(1) << "\t" << frm_state(2)
- << "\t" << frm_state(3) << "\t" << frm_state(4) << "\t" << frm_state(5) << "\t" << frm_state(6)
- << "\t" << frm_state(7) << "\t" << frm_state(8) << "\t" << frm_state(9)
- << "\t" << frm_state(10) << "\t" << frm_state(11) << "\t" << frm_state(12) << "\t" << frm_state(13) << "\t" << frm_state(14) << "\t" << frm_state(15) << std::endl;
- }
-
- #endif
- }
-
- clock_t end = clock();
- FrameIMUPtr last_KF = std::static_pointer_cast<FrameIMU>(wolf_problem_ptr_->getTrajectory()->closestKeyFrameToTimeStamp(ts));
-
- //closing file
- imu_data_input.close();
- odom_data_input.close();
-
- #ifdef KF0_EVOLUTION
- KF0_evolution.close();
- #endif
-
- //===================================================== END{PROCESS DATA}
-
- double elapsed_secs = double(end - begin) / CLOCKS_PER_SEC;
-
- // Final state
- std::cout << "\nIntegration results ----------------------------------------------------------------------------------------------" << std::endl;
- std::cout << "Initial state: " << std::fixed << std::setprecision(3) << std::setw(8)
- << x_origin.head(16).transpose() << std::endl;
- std::cout << "Integrated delta: " << std::fixed << std::setprecision(3) << std::setw(8)
- << wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_.transpose() << std::endl;
- std::cout << "Integrated state: " << std::fixed << std::setprecision(3) << std::setw(8)
- << wolf_problem_ptr_->getProcessorMotion()->getCurrentState().head(16).transpose() << std::endl;
- std::cout << "Integrated std : " << std::fixed << std::setprecision(3) << std::setw(8)
- << (wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_cov_.diagonal()).array().sqrt() << std::endl;
-
- // Print statistics
- std::cout << "\nStatistics -----------------------------------------------------------------------------------" << std::endl;
- std::cout << "If you want meaningful CPU metrics, remove all couts in the loop / remove DEBUG_RESULTS definition variable, and compile in RELEASE mode!" << std::endl;
-
- TimeStamp t0, tf;
- t0 = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().front().ts_;
- tf = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
- int N = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().size();
- std::cout << "t0 : " << t0.get() << " s" << std::endl;
- std::cout << "tf : " << tf.get() << " s" << std::endl;
- std::cout << "duration : " << tf-t0 << " s" << std::endl;
- std::cout << "N samples : " << N << std::endl;
- std::cout << "frequency : " << (N-1)/(tf-t0) << " Hz" << std::endl;
- std::cout << "CPU time : " << elapsed_secs << " s" << std::endl;
- std::cout << "s/integr : " << elapsed_secs/(N-1)*1e6 << " us" << std::endl;
- std::cout << "integr/s : " << (N-1)/elapsed_secs << " ips" << std::endl;
-
- //fix parts of the problem if needed
- origin_KF->getP()->fix();
- origin_KF->getO()->fix();
- origin_KF->getV()->fix();
-
-
- std::cout << "\t\t\t ______solving______" << std::endl;
- std::string report = ceres_manager_wolf_diff->solve(SolverManager::ReportVerbosity::FULL); //0: nothing, 1: BriefReport, 2: FullReport
- std::cout << report << std::endl;
-
- last_KF->getAccBias()->fix();
- last_KF->getGyroBias()->fix();
-
- std::cout << "\t\t\t solving after fixBias" << std::endl;
- report = ceres_manager_wolf_diff->solve(SolverManager::ReportVerbosity::BRIEF); //0: nothing, 1: BriefReport, 2: FullReport
- std::cout << report << std::endl;
- ceres_manager_wolf_diff->computeCovariances(SolverManager::CovarianceBlocksToBeComputed::ALL);
- std::cout << "\t\t\t ______solved______" << std::endl;
-
- wolf_problem_ptr_->print(4,1,1,1);
-
- #ifdef DEBUG_RESULTS
- Eigen::VectorXs frm_state(16);
- Eigen::Matrix<wolf::Scalar, 16, 1> cov_stdev;
- Eigen::MatrixXs covX(16,16);
- Eigen::MatrixXs cov3(Eigen::Matrix3s::Zero());
-
- wolf::FrameBasePtrList frame_list = wolf_problem_ptr_->getTrajectory()->getFrameList();
- for(FrameBasePtr frm_ptr : frame_list)
- {
- if(frm_ptr->isKey())
- {
- //prepare needed variables
- FrameIMUPtr frmIMU_ptr = std::static_pointer_cast<FrameIMU>(frm_ptr);
- frm_state = frmIMU_ptr->getState();
- ts = frmIMU_ptr->getTimeStamp();
-
- //get data from covariance blocks
- wolf_problem_ptr_->getFrameCovariance(frmIMU_ptr, covX);
- wolf_problem_ptr_->getCovarianceBlock(frmIMU_ptr->getV(), frmIMU_ptr->getV(), cov3);
- covX.block(7,7,3,3) = cov3;
- wolf_problem_ptr_->getCovarianceBlock(frmIMU_ptr->getAccBias(), frmIMU_ptr->getAccBias(), cov3);
- covX.block(10,10,3,3) = cov3;
- wolf_problem_ptr_->getCovarianceBlock(frmIMU_ptr->getGyroBias(), frmIMU_ptr->getGyroBias(), cov3);
- covX.block(13,13,3,3) = cov3;
- for(int i = 0; i<16; i++)
- cov_stdev(i) = ( covX(i,i)? 2*sqrt(covX(i,i)):0); //if diagonal value is 0 then store 0 else store 2*sqrt(diag_value)
-
- debug_results << std::setprecision(16) << ts.get() << "\t" << frm_state(0) << "\t" << frm_state(1) << "\t" << frm_state(2)
- << "\t" << frm_state(3) << "\t" << frm_state(4) << "\t" << frm_state(5) << "\t" << frm_state(6)
- << "\t" << frm_state(7) << "\t" << frm_state(8) << "\t" << frm_state(9)
- << "\t" << frm_state(10) << "\t" << frm_state(11) << "\t" << frm_state(12) << "\t" << frm_state(13) << "\t" << frm_state(14) << "\t" << frm_state(15)
- << "\t" << cov_stdev(0) << "\t" << cov_stdev(1) << "\t" << cov_stdev(2)
- << "\t" << cov_stdev(3) << "\t" << cov_stdev(4) << "\t" << cov_stdev(5) << "\t" << cov_stdev(6)
- << "\t" << cov_stdev(7) << "\t" << cov_stdev(8) << "\t" << cov_stdev(9)
- << "\t" << cov_stdev(10) << "\t" << cov_stdev(11) << "\t" << cov_stdev(12) << "\t" << cov_stdev(13) << "\t" << cov_stdev(14) << "\t" << cov_stdev(15) << std::endl;
- }
- }
-
- //trials to print all factorIMUs' residuals
- Eigen::Matrix<wolf::Scalar,15,1> IMU_residuals;
- Eigen::Vector3s p1(Eigen::Vector3s::Zero());
- Eigen::Vector4s q1_vec(Eigen::Vector4s::Zero());
- Eigen::Map<Quaternions> q1(q1_vec.data());
- Eigen::Vector3s v1(Eigen::Vector3s::Zero());
- Eigen::Vector3s ab1(Eigen::Vector3s::Zero());
- Eigen::Vector3s wb1(Eigen::Vector3s::Zero());
- Eigen::Vector3s p2(Eigen::Vector3s::Zero());
- Eigen::Vector4s q2_vec(Eigen::Vector4s::Zero());
- Eigen::Map<Quaternions> q2(q2_vec.data());
- Eigen::Vector3s v2(Eigen::Vector3s::Zero());
- Eigen::Vector3s ab2(Eigen::Vector3s::Zero());
- Eigen::Vector3s wb2(Eigen::Vector3s::Zero());
-
- for(FrameBasePtr frm_ptr : frame_list)
- {
- if(frm_ptr->isKey())
- {
- FactorBasePtrList fac_list = frm_ptr->getConstrainedByList();
- for(FactorBasePtr fac_ptr : fac_list)
- {
- if(fac_ptr->getTypeId() == FAC_IMU)
- {
- //Eigen::VectorXs prev_KF_state(fac_ptr->getFrameOther()->getState());
- //Eigen::VectorXs curr_KF_state(fac_ptr->getFeature()->getFrame()->getState());
- p1 = fac_ptr->getFrameOther()->getP()->getState();
- q1_vec = fac_ptr->getFrameOther()->getO()->getState();
- v1 = fac_ptr->getFrameOther()->getV()->getState();
- ab1 = std::static_pointer_cast<FrameIMU>(fac_ptr->getFrameOther())->getAccBias()->getState();
- wb1 = std::static_pointer_cast<FrameIMU>(fac_ptr->getFrameOther())->getGyroBias()->getState();
-
- p2 = fac_ptr->getFeature()->getFrame()->getP()->getState();
- q2_vec = fac_ptr->getFeature()->getFrame()->getO()->getState();
- v2 = fac_ptr->getFeature()->getFrame()->getV()->getState();
- ab2 = std::static_pointer_cast<FrameIMU>(fac_ptr->getFeature()->getFrame())->getAccBias()->getState();
- wb2 = std::static_pointer_cast<FrameIMU>(fac_ptr->getFeature()->getFrame())->getGyroBias()->getState();
-
- std::static_pointer_cast<FactorIMU>(fac_ptr)->residual(p1, q1, v1, ab1, wb1, p2, q2, v2, ab2, wb2, IMU_residuals);
- std::cout << "IMU residuals : " << IMU_residuals.transpose() << std::endl;
- }
- }
- }
- }
-
- debug_results.close();
- WOLF_WARN("WARNING : DEBUG_RESULTS ACTIVATED - slows the process (writing results to result_debugs.dat file)")
-
- #endif
-
- return 0;
-
-}
-
-int _kbhit()
-{
- struct timeval tv;
- fd_set fds;
- tv.tv_sec = 0;
- tv.tv_usec = 0;
- FD_ZERO(&fds);
- FD_SET(STDIN_FILENO, &fds); //STDIN_FILENO is 0
- select(STDIN_FILENO+1, &fds, NULL, NULL, &tv);
- return FD_ISSET(STDIN_FILENO, &fds);
-}
diff --git a/demos/demo_kf_callback.cpp b/demos/demo_kf_callback.cpp
deleted file mode 100644
index 9e01558e3..000000000
--- a/demos/demo_kf_callback.cpp
+++ /dev/null
@@ -1,72 +0,0 @@
-/*
- * test_kf_callback.cpp
- *
- * Created on: Nov 6, 2016
- * Author: jsola
- */
-
-#include "core/sensor/sensor_odom_2D.h"
-#include "core/processor/processor_odom_2D.h"
-#include "core/processor/processor_tracker_feature_dummy.h"
-#include "core/capture/capture_void.h"
-
-int main()
-{
- using namespace wolf;
- using namespace Eigen;
- using namespace std;
-
- ProblemPtr problem = Problem::create("PO", 2);
-
- SensorBasePtr sen_odo = problem->installSensor ("ODOM 2D", "main odometer", (Vector3s()<<0,0,0).finished(),"");
- ProcessorParamsOdom2DPtr params_odo = std::make_shared<ProcessorParamsOdom2D>();
- params_odo->max_time_span = 2;
- params_odo->angle_turned = M_PI; // 180 degrees turn
- ProcessorBasePtr prc_odo = problem->installProcessor("ODOM 2D", "odometry integrator", sen_odo, params_odo);
- prc_odo->setTimeTolerance(0.1);
-
- SensorBasePtr sen_ftr = problem->installSensor ("ODOM 2D", "other odometer", (Vector3s()<<0,0,0).finished(),"");
- ProcessorParamsTrackerFeaturePtr params_trk = std::make_shared<ProcessorParamsTrackerFeature>();
- params_trk->max_new_features = 4;
- params_trk->min_features_for_keyframe = 7;
- params_trk->time_tolerance = 0.5;
- shared_ptr<ProcessorTrackerFeatureDummy> prc_ftr = make_shared<ProcessorTrackerFeatureDummy>(params_trk);
- prc_ftr->setName("tracker");
- sen_ftr->addProcessor(prc_ftr);
- prc_ftr->setTimeTolerance(0.1);
-
- cout << "Motion sensor : " << problem->getProcessorMotion()->getSensor()->getName() << endl;
- cout << "Motion processor : " << problem->getProcessorMotion()->getName() << endl;
-
- TimeStamp t(0);
- cout << "=======================\n>> TIME: " << t.get() << endl;
- Vector3s x({0,0,0});
- Matrix3s P; P.setZero();
- problem->setPrior(x, P, t, 0.01);
-
- cout << "x(" << t.get() << ") = " << problem->getCurrentState().transpose() << endl;
-
- Vector2s odo_data; odo_data << .1, (M_PI / 10);
-
- problem->print(2, false, true, true); // print(level, constr_by, metric, state_blocks)
-
- Scalar dt = 1;
- for (auto i = 0; i < 4; i++)
- {
-
- cout << "Tracker----------------" << endl;
- sen_ftr->process(make_shared<CaptureVoid>(t, sen_ftr));
- problem->print(2, false, true, true); // print(level, constr_by, metric, state_blocks)
-
- t += dt;
- cout << "=======================\n>> TIME: " << t.get() << endl;
-
- cout << "Motion-----------------" << endl;
- sen_odo->process(make_shared<CaptureMotion>("ODOM 2D", t, sen_odo, odo_data, 3, 3, nullptr));
- cout << "x(" << t.get() << ") = " << problem->getCurrentState().transpose() << endl;
- problem->print(2, false, true, true); // print(level, constr_by, metric, state_blocks)
-
- }
-
- return 0;
-}
diff --git a/demos/demo_list_remove.cpp b/demos/demo_list_remove.cpp
deleted file mode 100644
index b0795d0a6..000000000
--- a/demos/demo_list_remove.cpp
+++ /dev/null
@@ -1,61 +0,0 @@
-/*
- * test_list_remove.cpp
- *
- * Created on: Nov 19, 2016
- * Author: jsola
- */
-
-#include <memory>
-#include <list>
-#include <algorithm>
-#include <iostream>
-
-int main()
-{
- using std::list;
- using std::shared_ptr;
- using std::make_shared;
- using std::cout;
- using std::endl;
-
- typedef shared_ptr<int> IntPtr;
-
- list<IntPtr> L;
-
- L.push_back(make_shared<int>(0));
- L.push_back(make_shared<int>(1));
- L.push_back(make_shared<int>(2));
-
- cout << "size: " << L.size() << endl;
-
-// for (auto p : L)
-// {
-// cout << "removing " << *p << endl;
-// L.remove(p);
-// cout << "size: " << L.size() << endl;
-// }
-
-// list<IntPtr>::iterator it = L.begin();
-// while (it != L.end())
-// {
-// cout << "removing " << **it << endl;
-// L.erase(it);
-// it = L.begin();
-// cout << "size: " << L.size() << endl;
-// }
-
- list<IntPtr> L_black;
- for (auto p : L)
- {
- cout << "marking " << *p << endl;
- L_black.push_back(p);
- cout << "size: " << L.size() << endl;
- }
- for (auto p : L_black)
- {
- cout << "removing " << *p << endl;
- L.remove(p);
- cout << "size: " << L.size() << endl;
- }
- return 0;
-}
diff --git a/demos/demo_map_yaml.cpp b/demos/demo_map_yaml.cpp
deleted file mode 100644
index 159ce8532..000000000
--- a/demos/demo_map_yaml.cpp
+++ /dev/null
@@ -1,101 +0,0 @@
-/**
- * \file test_map_yaml.cpp
- *
- * Created on: Jul 27, 2016
- * \author: jsola
- */
-
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/map/map_base.h"
-#include "base/landmark/landmark_polyline_2D.h"
-#include "base/landmark/landmark_AHP.h"
-#include "base/state_block/state_block.h"
-#include "base/yaml/yaml_conversion.h"
-
-#include <iostream>
-using namespace wolf;
-
-void print(MapBase& _map)
-{
- for (auto lmk_ptr : _map.getLandmarkList())
- {
- std::cout << "Lmk ID: " << lmk_ptr->id();
- std::cout << "\nLmk type: " << lmk_ptr->getType();
- if (lmk_ptr->getType() == "POLYLINE 2D")
- {
- LandmarkPolyline2DPtr poly_ptr = std::static_pointer_cast<LandmarkPolyline2D>(lmk_ptr);
- std::cout << "\npos: " << poly_ptr->getP()->getState().transpose() << " -- fixed: " << poly_ptr->getP()->isFixed();
- std::cout << "\nori: " << poly_ptr->getO()->getState().transpose() << " -- fixed: " << poly_ptr->getO()->isFixed();
- std::cout << "\nn points: " << poly_ptr->getNPoints();
- std::cout << "\nFirst idx: " << poly_ptr->getFirstId();
- std::cout << "\nFirst def: " << poly_ptr->isFirstDefined();
- std::cout << "\nLast def: " << poly_ptr->isLastDefined();
- for (int idx = poly_ptr->getFirstId(); idx <= poly_ptr->getLastId(); idx++)
- std::cout << "\n point: " << idx << ": " << poly_ptr->getPointStateBlock(idx)->getState().transpose();
- break;
- }
- else if (lmk_ptr->getType() == "AHP")
- {
- LandmarkAHPPtr ahp_ptr = std::static_pointer_cast<LandmarkAHP>(lmk_ptr);
- std::cout << "\npos: " << ahp_ptr->getP()->getState().transpose() << " -- fixed: " << ahp_ptr->getP()->isFixed();
- std::cout << "\ndescript: " << ahp_ptr->getCvDescriptor().t();
- break;
- }
- else
- break;
-
- std::cout << std::endl;
- }
-}
-
-int main()
-{
- using namespace Eigen;
-
- std::cout << "\nTesting Lmk creator and node saving..." << std::endl;
- Vector4s v;
- v << 1, 2, 3, 4;
- cv::Mat d = (cv::Mat_<int>(8,1) << 1, 2, 3, 4, 5, 6, 7, 8);
- LandmarkAHP lmk_1(v, nullptr, nullptr, d);
- std::cout << "Pos 1 = " << lmk_1.getP()->getState().transpose() << std::endl;
- std::cout << "Des 1 = " << lmk_1.getCvDescriptor().t() << std::endl;
-
- YAML::Node n = lmk_1.saveToYaml();
- std::cout << "Pos n = " << n["position"].as<VectorXs>().transpose() << std::endl;
- std::cout << "Des n = " << n["descriptor"].as<VectorXs>().transpose() << std::endl;
-
- LandmarkAHP lmk_2 = *(std::static_pointer_cast<LandmarkAHP>(LandmarkAHP::create(n)));
- std::cout << "Pos 2 = " << lmk_2.getP()->getState().transpose() << std::endl;
- std::cout << "Des 2 = " << lmk_2.getCvDescriptor().t() << std::endl;
-
- std::string filename;
-
- std::string wolf_root = _WOLF_ROOT_DIR;
- std::string wolf_config = wolf_root + "/src/examples";
- std::cout << "\nWolf directory for configuration files: " << wolf_config << std::endl;
-
- ProblemPtr problem = Problem::create("PO", 2);
- filename = wolf_config + "/map_polyline_example.yaml";
- std::cout << "Reading map from file: " << filename << std::endl;
- problem->loadMap(filename);
-
- std::cout << "Printing map..." << std::endl;
- print(*(problem->getMap()));
-
- filename = wolf_config + "/map_polyline_example_write.yaml";
- std::cout << "Writing map to file: " << filename << std::endl;
- std::string thisfile = __FILE__;
- problem->getMap()->save(filename, "Example generated by test file " + thisfile);
-
- std::cout << "Clearing map... " << std::endl;
- problem->getMap()->getLandmarkList().clear();
-
- std::cout << "Re-reading map from file: " << filename << std::endl;
- problem->loadMap(filename);
-
- std::cout << "Printing map..." << std::endl;
- print(*(problem->getMap()));
-
- return 0;
-}
diff --git a/demos/demo_matrix_prod.cpp b/demos/demo_matrix_prod.cpp
deleted file mode 100644
index b03068283..000000000
--- a/demos/demo_matrix_prod.cpp
+++ /dev/null
@@ -1,187 +0,0 @@
-/**
- * \file test_matrix_prod.cpp
- *
- * Created on: May 26, 2016
- * \author: jsola
- */
-
-#include "eigen3/Eigen/Dense"
-
-//std includes
-#include <ctime>
-#include <iostream>
-#include <iomanip>
-
-#include <eigen3/Eigen/StdVector>
-using namespace Eigen;
-
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,1,1,RowMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,2,2,RowMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,3,3,RowMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,4,4,RowMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,5,5,RowMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,6,6,RowMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,7,7,RowMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,8,8,RowMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,9,9,RowMajor>)
-
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,1,1,ColMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,2,2,ColMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,3,3,ColMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,4,4,ColMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,5,5,ColMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,6,6,ColMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,7,7,ColMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,8,8,ColMajor>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,9,9,ColMajor>)
-
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,2,1>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,3,1>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,4,1>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,5,1>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,6,1>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,7,1>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,8,1>)
-EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(Eigen::Matrix<double,9,1>)
-
-#define DECLARE_MATRICES(s) \
- Matrix<double, s, s, RowMajor> R1, R2, Ro; \
- Matrix<double, s, s, ColMajor> C1, C2, Co;
-
-#define INIT_MATRICES(s) \
- R1.setRandom(s, s);\
- R2.setRandom(s, s);\
- C1.setRandom(s, s);\
- C2.setRandom(s, s);\
- Ro.setRandom(s, s);\
- Co.setRandom(s, s);
-
-#define LOOP_MATRIX(N,Mo,M1,M2) \
- for (int i = 0; i < N; i++) \
- { \
- Mo = M1 * M2; \
- M1(2,2) = Mo(2,2); \
- }
-
-#define EVALUATE_MATRIX(N,Mo,M1,M2) \
- t0 = clock(); \
- LOOP_MATRIX(N,Mo,M1,M2) \
- t1 = clock(); \
- std::cout << std::setw(15) << Mo(2,2) << "\t";
-
-#define EVALUATE_ALL \
- EVALUATE_MATRIX(N, Ro, R1, R2)\
- std::cout << "Time Ro = R * R: " << (long double)(t1 - t0) * 1e9 / CLOCKS_PER_SEC / N << "ns" << std::endl;\
- EVALUATE_MATRIX(N, Ro, R1, C2)\
- std::cout << "Time Ro = R * C: " << (long double)(t1 - t0) * 1e9 / CLOCKS_PER_SEC / N << "ns" << std::endl;\
- EVALUATE_MATRIX(N, Ro, C1, R2)\
- std::cout << "Time Ro = C * R: " << (long double)(t1 - t0) * 1e9 / CLOCKS_PER_SEC / N << "ns" << std::endl;\
- EVALUATE_MATRIX(N, Ro, C1, C2)\
- std::cout << "Time Ro = C * C: " << (long double)(t1 - t0) * 1e9 / CLOCKS_PER_SEC / N << "ns" << std::endl;\
- EVALUATE_MATRIX(N, Co, R1, R2)\
- std::cout << "Time Co = R * R: " << (long double)(t1 - t0) * 1e9 / CLOCKS_PER_SEC / N << "ns" << std::endl;\
- EVALUATE_MATRIX(N, Co, R1, C2)\
- std::cout << "Time Co = R * C: " << (long double)(t1 - t0) * 1e9 / CLOCKS_PER_SEC / N << "ns" << std::endl;\
- EVALUATE_MATRIX(N, Co, C1, R2)\
- std::cout << "Time Co = C * R: " << (long double)(t1 - t0) * 1e9 / CLOCKS_PER_SEC / N << "ns" << std::endl;\
- EVALUATE_MATRIX(N, Co, C1, C2)\
- std::cout << "Time Co = C * C: " << (long double)(t1 - t0) * 1e9 / CLOCKS_PER_SEC / N \
- << "ns <-- this is the Eigen default!" << std::endl;
-
-/**
- * We multiply matrices and see how long it takes.
- * We compare different combinations of row-major and column-major to see which one is the fastest.
- * We can select the matrix size.
- */
-int main()
-{
- using namespace Eigen;
-
- int N = 100*1000;
- const int S = 6;
- Matrix<double, 16, S - 3 + 1> results;
- clock_t t0, t1;
-
- // All dynamic sizes
- {
- Matrix<double, Dynamic, Dynamic, RowMajor> R1, R2, Ro;
- Matrix<double, Dynamic, Dynamic, ColMajor> C1, C2, Co;
-
- for (int s = 3; s <= S; s++)
- {
- std::cout << "Timings for dynamic matrix product. R: row major matrix. C: column major matrix. " << s << "x"
- << s << " matrices." << std::endl;
-
- INIT_MATRICES(s)
- EVALUATE_ALL
-
- }
- }
- // Statics, one by one
- {
- const int s = 3;
- std::cout << "Timings for static matrix product. R: row major matrix. C: column major matrix. " << s << "x" << s
- << " matrices." << std::endl;
-
- DECLARE_MATRICES(s)
- INIT_MATRICES(s)
- EVALUATE_ALL
- }
- {
- const int s = 4;
- std::cout << "Timings for static matrix product. R: row major matrix. C: column major matrix. " << s << "x" << s
- << " matrices." << std::endl;
-
- DECLARE_MATRICES(s)
- INIT_MATRICES(s)
- EVALUATE_ALL
- }
- {
- const int s = 5;
- std::cout << "Timings for static matrix product. R: row major matrix. C: column major matrix. " << s << "x" << s
- << " matrices." << std::endl;
-
- DECLARE_MATRICES(s)
- INIT_MATRICES(s)
- EVALUATE_ALL
- }
- {
- const int s = 6;
- std::cout << "Timings for static matrix product. R: row major matrix. C: column major matrix. " << s << "x" << s
- << " matrices." << std::endl;
-
- DECLARE_MATRICES(s)
- INIT_MATRICES(s)
- EVALUATE_ALL
- }
-
- std::cout << "Test q and R rotations" << std::endl;
- Eigen::Quaterniond q(Eigen::Vector4d::Random().normalized());
- Eigen::Matrix3d R = q.matrix();
- Eigen::Vector3d v0; v0.setRandom(); v0.normalize(); double v0n = v0.norm();
- Eigen::Vector3d v;
-
- N *= 100;
-
- v = v0;
- t0 = clock();
- for (int i = 0; i < N; i++)
- {
- v = R * v;
- }
- t1 = clock();
- std::cout << "Time w = R * v: " << (double)(t1 - t0) * 1e9 / CLOCKS_PER_SEC / N << "ns" << std::endl;
- std::cout << "v norm change: " << 10*logl((long double)v.norm()/(long double)v0n) << " dB" << std::endl;
-
- v = v0;
- t0 = clock();
- for (int i = 0; i < N; i++)
- {
- v = q * v;
- }
- t1 = clock();
- std::cout << "Time w = q * v: " << (double)(t1 - t0) * 1e9 / CLOCKS_PER_SEC / N << "ns" << std::endl;
- std::cout << "v norm change: " << 10*logl((long double)v.norm()/(long double)v0n) << " dB" << std::endl;
- return 0;
-}
-
diff --git a/demos/demo_mpu.cpp b/demos/demo_mpu.cpp
deleted file mode 100644
index 1fbed214f..000000000
--- a/demos/demo_mpu.cpp
+++ /dev/null
@@ -1,233 +0,0 @@
-/**
- * \file test_mpu.cpp
- *
- * Created on: Oct 4, 2016
- * \author: AtDinesh
- */
-
- //Wolf
-#include "base/capture/capture_IMU.h"
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/state_block/state_block.h"
-#include "base/state_block/state_quaternion.h"
-#include <iostream>
-#include <fstream>
-#include <iomanip>
-#include <ctime>
-#include <cmath>
-#include <termios.h>
-#include <fcntl.h>
-#include "base/processor/processor_IMU.h"
-#include "base/sensor/sensor_IMU.h"
-
-#define DEBUG_RESULTS
-#define FROM_FILE
-
-int _kbhit();
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- #ifdef FROM_FILE
- std::ifstream data_file;
- const char * filename;
-
- if (argc < 2)
- {
- std::cout << "Missing input argument! : needs 1 argument (path to data file)." << std::endl;
- return 1;
- }
- else
- {
- filename = argv[1];
- data_file.open(filename);
- std::cout << "file: " << filename << std::endl;
-
- std::string dummy;
- getline(data_file, dummy);
-
- if(!data_file.is_open()){
- std::cerr << "Failed to open data files... Exiting" << std::endl;
- return 1;
- }
- }
- #else
- int fd,n;
- ///prepare MPU here
- if (argc < 2)
- {
- std::cout << "Missing input argument! : needs 1 argument : way to MPU device. (usually /dev/ttyACM#)\n Please make sure that you have rights to access the device and that your user belongs to the dialout group." << std::endl;
- return 1;
- }
- unsigned char buf[64] = {0};
- wolf::Scalar gravity = 9.81;
- wolf::Scalar sec_to_rad = 3.14159265359/180.0;
- wolf::Scalar accel_LSB = 1.0/8192.0; // = 4.0/32768.0
- wolf::Scalar gyro_LSB = 1.0/131.0; // = 250.0/32768.0
- wolf::Scalar accel_LSB_g = accel_LSB * gravity;
- wolf::Scalar gyro_LSB_rad = gyro_LSB * sec_to_rad;
- //wolf::Scalar Ax, Ay, Az, Gx, Gy, Gz;
-
- struct termios toptions;
- //open serial port
- std::cout << "open port...\n" << std::endl;
- fd = open(argv[1], O_RDWR | O_NOCTTY);
- if (fd != -1)
- std::cout << "MPU openned successfully! \n" << std::endl;
- else
- std::cout << "MPU could not be openned... \n" << std::endl;
-
- //configuring termios
- tcgetattr(fd, &toptions);
- cfsetispeed(&toptions, B1000000);
- cfsetospeed(&toptions, B1000000);
- toptions.c_cflag |= (CLOCAL | CREAD);
- toptions.c_lflag &= ~(ICANON | ECHO | ECHOE | ISIG);
- toptions.c_oflag &= ~OPOST;
- toptions.c_cc[VMIN] = 0;
- toptions.c_cc[VTIME] = 10;
- tcsetattr(fd, TCSANOW, &toptions);
- #endif
-
- #ifdef DEBUG_RESULTS
- std::ofstream debug_results;
- debug_results.open("debug_results.dat");
- if(debug_results)
- debug_results << "%%TimeStamp\t"
- << "dp_x\t" << "dp_y\t" << "dp_z\t" << "dv_x\t" << "dv_y\t" << "dv_z\t" << "dq_x\t" << "dq_y\t" << "dq_z\t" << "dq_w\t"
- << "Dp_x\t" << "Dp_y\t" << "Dp_z\t" << "Dv_x\t" << "Dv_y\t" << "Dv_z\t" << "Dq_x\t" << "Dq_y\t" << "Dq_z\t" << "Dq_w\t"
- << "X_x\t" << "X_y\t" << "X_z\t" << "Xv_x\t" << "Xv_y\t" << "Xv_z\t" << "Xq_x\t" << "Xq_y\t" << "Xq_z\t" << "Xq_w\t" << std::endl;
- #endif
-
- // Wolf problem
- ProblemPtr wolf_problem_ptr_ = Problem::create("PQVBB 3D");
- Eigen::VectorXs IMU_extrinsics(7);
- IMU_extrinsics << 0,0,0, 0,0,0,1; // IMU pose in the robot
- SensorBasePtr sensor_ptr = wolf_problem_ptr_->installSensor("IMU", "Main IMU", IMU_extrinsics, IntrinsicsBase());
- wolf_problem_ptr_->installProcessor("IMU", "IMU pre-integrator", "Main IMU", "");
-
- // Time and data variables
- TimeStamp t;
- Eigen::Vector6s data_;
- Scalar mpu_clock = 0;
-
- t.set(mpu_clock * 0.0001); // clock in 0,1 ms ticks
-
- // Set the origin
- Eigen::VectorXs x0(16);
- x0 << 0,0,0, 0,0,0, 1,0,0,0, 0,0,.001, 0,0,.002; // Try some non-zero biases
- wolf_problem_ptr_->getProcessorMotion()->setOrigin(x0, t);
-
- // Create one capture to store the IMU data arriving from (sensor / callback / file / etc.)
- CaptureIMUPtr imu_ptr( std::make_shared<CaptureIMU>(t, sensor_ptr, data_) );
-
- // main loop
- using namespace std;
- clock_t begin = clock();
- std::cout << "\n\t\t\t\tENTERING MAIN LOOP - Please press ENTER to exit loop\n" << std::endl;
-
- #ifdef FROM_FILE
- while(!data_file.eof()){
- // read new data
- data_file >> mpu_clock >> data_[0] >> data_[1] >> data_[2] >> data_[3] >> data_[4] >> data_[5];
- t.set(mpu_clock); //
- #else
- while(!_kbhit()){
- // read new data
- do n = read(fd, buf, 1);//READ IT
- while (buf[0]!=0x47); //control character has been found
- n = read(fd, buf, 12);//read the data
- if (n>3){ //construct data_ from IMU input
- data_(0) = (wolf::Scalar)((int16_t)((buf[1]<<8)|buf[0]))*accel_LSB_g;
- data_(1) = (wolf::Scalar)((int16_t)((buf[3]<<8)|buf[2]))*accel_LSB_g;
- data_(2) = (wolf::Scalar)((int16_t)((buf[5]<<8)|buf[4]))*accel_LSB_g;
- data_(3) = (wolf::Scalar)((int16_t)((buf[7]<<8)|buf[6]))*gyro_LSB_rad;
- data_(4) = (wolf::Scalar)((int16_t)((buf[9]<<8)|buf[8]))*gyro_LSB_rad;
- data_(5) = (wolf::Scalar)((int16_t)((buf[11]<<8)|buf[10]))*gyro_LSB_rad;
- mpu_clock += 0.001;
- t.set(mpu_clock);
- }
- #endif
-
- // assign data to capture
- imu_ptr->setData(data_);
- imu_ptr->setTimeStamp(t);
-
- // process data in capture
- sensor_ptr->process(imu_ptr);
-
- #ifdef DEBUG_RESULTS
-
- Eigen::VectorXs delta_debug;
- Eigen::VectorXs delta_integr_debug;
- Eigen::VectorXs x_debug;
- TimeStamp ts;
-
- delta_debug = wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_;
- delta_integr_debug = wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_;
- x_debug = wolf_problem_ptr_->getProcessorMotion()->getCurrentState();
- ts = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
-
- if(debug_results)
- debug_results << ts.get() << "\t" << delta_debug(0) << "\t" << delta_debug(1) << "\t" << delta_debug(2) << "\t" << delta_debug(3) << "\t" << delta_debug(4) << "\t"
- << delta_debug(5) << "\t" << delta_debug(6) << "\t" << delta_debug(7) << "\t" << delta_debug(8) << "\t" << delta_debug(9) << "\t"
- << delta_integr_debug(0) << "\t" << delta_integr_debug(1) << "\t" << delta_integr_debug(2) << "\t" << delta_integr_debug(3) << "\t" << delta_integr_debug(4) << "\t"
- << delta_integr_debug(5) << "\t" << delta_integr_debug(6) << "\t" << delta_integr_debug(7) << "\t" << delta_integr_debug(8) << "\t" << delta_integr_debug(9) << "\t"
- << x_debug(0) << "\t" << x_debug(1) << "\t" << x_debug(2) << "\t" << x_debug(3) << "\t" << x_debug(4) << "\t"
- << x_debug(5) << "\t" << x_debug(6) << "\t" << x_debug(7) << "\t" << x_debug(8) << "\t" << x_debug(9) << "\n";
- #endif
- }
-
- clock_t end = clock();
- double elapsed_secs = double(end - begin) / CLOCKS_PER_SEC;
-
- // Final state
- std::cout << "\nIntegration results ----------------------------------------------------------------------------------------------" << std::endl;
- std::cout << "Initial state: " << std::fixed << std::setprecision(3) << std::setw(8)
- << x0.head(16).transpose() << std::endl;
- std::cout << "Integrated delta: " << std::fixed << std::setprecision(3) << std::setw(8)
- << wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_.transpose() << std::endl;
- std::cout << "Integrated state: " << std::fixed << std::setprecision(3) << std::setw(8)
- << wolf_problem_ptr_->getProcessorMotion()->getCurrentState().head(16).transpose() << std::endl;
- std::cout << "Integrated std : " << std::fixed << std::setprecision(3) << std::setw(8)
- << (wolf_problem_ptr_->getProcessorMotion()->getMotion().delta_integr_cov_.diagonal().transpose()).array().sqrt() << std::endl;
-
- // Print statistics
- std::cout << "\nStatistics -----------------------------------------------------------------------------------" << std::endl;
- std::cout << "If you want meaningful CPU metrics, remove all couts in the loop / remove DEBUG_RESULTS definition variable, and compile in RELEASE mode!" << std::endl;
-
-#ifdef DEBUG_RESULTS
- std::cout << "\t\tWARNING : DEBUG_RESULTS ACTIVATED - slows the process (writing results to result_debugs.dat file)" << std::endl;
- debug_results.close();
-#endif
-
- TimeStamp t0, tf;
- t0 = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().front().ts_;
- tf = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
- int N = wolf_problem_ptr_->getProcessorMotion()->getBuffer().get().size();
- std::cout << "t0 : " << t0.get() << " s" << std::endl;
- std::cout << "tf : " << tf.get() << " s" << std::endl;
- std::cout << "duration : " << tf-t0 << " s" << std::endl;
- std::cout << "N samples : " << N << std::endl;
- std::cout << "frequency : " << (N-1)/(tf-t0) << " Hz" << std::endl;
- std::cout << "CPU time : " << elapsed_secs << " s" << std::endl;
- std::cout << "s/integr : " << elapsed_secs/(N-1)*1e6 << " us" << std::endl;
- std::cout << "integr/s : " << (N-1)/elapsed_secs << " ips" << std::endl;
-
- return 0;
-
-}
-
-int _kbhit()
-{
- struct timeval tv;
- fd_set fds;
- tv.tv_sec = 0;
- tv.tv_usec = 0;
- FD_ZERO(&fds);
- FD_SET(STDIN_FILENO, &fds); //STDIN_FILENO is 0
- select(STDIN_FILENO+1, &fds, NULL, NULL, &tv);
- return FD_ISSET(STDIN_FILENO, &fds);
-}
diff --git a/demos/demo_polylines.cpp b/demos/demo_polylines.cpp
deleted file mode 100644
index 39943f932..000000000
--- a/demos/demo_polylines.cpp
+++ /dev/null
@@ -1,305 +0,0 @@
-// Sparsification example creating wolf tree from imported graph from .txt file
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-//std includes
-#include <cstdlib>
-#include <fstream>
-#include <string>
-#include <iostream>
-#include <memory>
-#include <random>
-#include <cmath>
-#include <queue>
-
-//Wolf includes
-#include "capture_void.h"
-#include "feature_odom_2D.h"
-#include "constraint_base.h"
-#include "ceres_wrapper/ceres_manager.h"
-
-// EIGEN
-//#include <Eigen/CholmodSupport>
-#include <Eigen/StdVector> // Eigen in std vector
-
-namespace wolf{
-
-void decodeEdge(const std::string& buffer, unsigned int& edge_from, unsigned int& edge_to, Eigen::Vector3s& measurement, Eigen::Matrix3s& covariance)
-{
- std::string str_num;
-
- unsigned int i = 0;
-
- // only decode edges
- if (buffer.at(0) == 'E')
- {
- //skip rest of EDGE word
- while (buffer.at(i) != ' ') i++;
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // FROM ID
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- edge_from = atoi(str_num.c_str())+1;
- str_num.clear();
-
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // TO ID
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- edge_to = atoi(str_num.c_str())+1;
- str_num.clear();
-
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // MEASUREMENT
- // X
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- measurement(0) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // Y
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- measurement(1) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // THETA
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- measurement(2) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // INFORMATION
- Eigen::Matrix3s information;
- // XX
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(0,0) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // XY
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(0,1) = atof(str_num.c_str());
- information(1,0) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // YY
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(1,1) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // THETATHETA
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(2,2) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // XTHETA
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(0,2) = atof(str_num.c_str());
- information(2,0) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // YTHETA
- while (i < buffer.size() && buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(1,2) = atof(str_num.c_str());
- information(2,1) = atof(str_num.c_str());
- str_num.clear();
-
- // COVARIANCE
- covariance = information.inverse();
- }
- else
- {
- edge_from = 0;
- edge_to = 0;
- }
-}
-
-}
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- //Welcome message
- std::cout << std::endl << " ========= WOLF IMPORTED .graph TEST ===========" << std::endl << std::endl;
-
- bool wrong_input = false;
- if (argc < 3)
- wrong_input = true;
- else if (argc > 4)
- wrong_input = true;
- else if (argc > 2 && (atoi(argv[2]) < 2 || atoi(argv[2]) > 5))
- wrong_input = true;
- else if (argc > 3 && atoi(argv[3]) < 0 )
- wrong_input = true;
-
- if (wrong_input)
- {
- std::cout << "Please call me with: [./test_wolf_imported_graph DATASET T (MAX_VERTICES)], where:" << std::endl;
- std::cout << " DATASET: manhattan, killian or intel" << std::endl;
- std::cout << " T keep one node each T: 2, 3, 4 or 5" << std::endl;
- std::cout << " optional: MAX_VERTICES max edges to be loaded" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
-
- // input variables
- char const * dataset_path = std::getenv("DATASET_PATH");
- unsigned int pruning_T = atoi(argv[2]);
- std::string file_path(dataset_path);
- file_path = file_path + "/graphs/redirected_" + std::to_string(pruning_T) + "_" + argv[1] + ".graph";
- unsigned int MAX_VERTEX = 1e9;
- if (argc > 3 && atoi(argv[3]) != 0)
- MAX_VERTEX = atoi(argv[3]);
-
- // Wolf problem
- FrameBasePtr last_frame_ptr, frame_from_ptr, frame_to_ptr;
- ProblemPtr bl_problem_ptr = Problem::create("PO_2D");
- SensorBasePtr sensor_ptr = bl_problem_ptr->installSensor("ODOM 2D", "Odometry", Eigen::VectorXs::Zero(3), IntrinsicsBasePtr());
-
- // Ceres wrapper
- std::string bl_summary, sp_summary;
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- ceres_options.max_num_iterations = 10;
- CeresManagerPtr bl_ceres_manager = std::make_shared<CeresManager>(bl_problem_ptr, ceres_options);
-
- // load graph from .txt
- std::ifstream graph_file;
- graph_file.open(file_path.c_str(), std::ifstream::in);
- if (!graph_file.is_open())
- {
- printf("\nError opening file: %s\n",file_path.c_str());
- return -1;
- }
-
- // auxiliar variables
- std::string line_string;
- unsigned int edge_from, edge_to;
- Eigen::Vector3s meas;
- Eigen::Matrix3s meas_cov;
- Eigen::Matrix3s R = Eigen::Matrix3s::Identity();
- //clock_t t1;
-
- // ------------------------ START EXPERIMENT ------------------------
- // First frame FIXED
- last_frame_ptr = bl_problem_ptr->emplaceFrame(KEY, Eigen::Vector3s::Zero(),TimeStamp(0));
- last_frame_ptr->fix();
- bl_problem_ptr->print(4, true, false, true);
-
- while (std::getline(graph_file, line_string) && last_frame_ptr->id() <= MAX_VERTEX)
- {
- std::cout << "new line:" << line_string << std::endl;
- decodeEdge(line_string, edge_from, edge_to, meas, meas_cov);
-
- // only factors
- if (edge_from != 0)
- {
-
- // ODOMETRY -------------------
- if (edge_to > last_frame_ptr->id())
- {
- frame_from_ptr = last_frame_ptr;
-
- // NEW KEYFRAME
- Eigen::Vector3s from_pose = frame_from_ptr->getState();
- R.topLeftCorner(2,2) = Eigen::Rotation2Ds(from_pose(2)).matrix();
- Eigen::Vector3s new_frame_pose = from_pose + R*meas;
- last_frame_ptr = bl_problem_ptr->emplaceFrame(KEY, new_frame_pose, TimeStamp(double(edge_to)));
-
- frame_to_ptr = last_frame_ptr;
-
- std::cout << "NEW FRAME " << last_frame_ptr->id() << " - ts = " << last_frame_ptr->getTimeStamp().get() << std::endl;
-
- // REMOVE PREVIOUS NODES
- }
- // LOOP CLOSURE ---------------
- else
- {
- if (edge_from == last_frame_ptr->id())
- frame_from_ptr = last_frame_ptr;
- else
- for (auto frm_rit = bl_problem_ptr->getTrajectoryPtr()->getFrameList().rbegin(); frm_rit != bl_problem_ptr->getTrajectoryPtr()->getFrameList().rend(); frm_rit++)
- if ((*frm_rit)->id() == edge_from)
- {
- frame_from_ptr = *frm_rit;
- break;
- }
- if (edge_to == last_frame_ptr->id())
- frame_to_ptr = last_frame_ptr;
- else
- for (auto frm_rit = bl_problem_ptr->getTrajectoryPtr()->getFrameList().rbegin(); frm_rit != bl_problem_ptr->getTrajectoryPtr()->getFrameList().rend(); frm_rit++)
- if ((*frm_rit)->id() == edge_to)
- {
- frame_to_ptr = *frm_rit;
- break;
- }
- }
-// std::cout << "frame_from " << frame_from_ptr->id() << std::endl;
-// std::cout << "edge_from " << edge_from << std::endl;
-// std::cout << "frame_to " << frame_to_ptr->id() << std::endl;
-// std::cout << "edge_to " << edge_to << std::endl;
-
- assert(frame_from_ptr->id() == edge_from && "frame from id and edge from idx must be the same");
- assert(frame_to_ptr->id() == edge_to && "frame to id and edge to idx must be the same");
-
- // CAPTURE
- CaptureVoidPtr capture_ptr = std::make_shared<CaptureVoid>(TimeStamp(0), sensor_ptr);
- frame_from_ptr->addCapture(capture_ptr);
-
- // FEATURE
- FeatureBasePtr feature_ptr = std::make_shared<FeatureOdom2D>(meas, meas_cov);
- capture_ptr->addFeature(feature_ptr);
-
- // CONSTRAINT
- ConstraintOdom2DPtr constraint_ptr = std::make_shared<ConstraintOdom2D>(feature_ptr, frame_to_ptr);
- feature_ptr->addConstraint(constraint_ptr);
- frame_to_ptr->addConstrainedBy(constraint_ptr);
-
- // SOLVE
- // solution
- bl_summary = bl_ceres_manager->solve(1);
- std::cout << bl_summary << std::endl;
-
- // covariance
- bl_ceres_manager->computeCovariances(ALL);//ALL_MARGINALS
-
-
- // t1 = clock();
- // double t_sigma_manual = 0;
- // t_sigma_manual += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- }
- }
-
- //bl_problem_ptr->print(4, true, false, true);
-
- //End message
- std::cout << " =========================== END ===============================" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_processor_imu.cpp b/demos/demo_processor_imu.cpp
deleted file mode 100644
index 33ec4cabb..000000000
--- a/demos/demo_processor_imu.cpp
+++ /dev/null
@@ -1,214 +0,0 @@
-/**
- * \file test_processor_imu.cpp
- *
- * Created on: Apr 12, 2016
- * \author: dtsbourg
- */
-
-//Wolf
-#include "base/capture/capture_IMU.h"
-#include "base/processor/processor_IMU.h"
-#include "base/sensor/sensor_IMU.h"
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/state_block/state_block.h"
-#include "base/state_block/state_quaternion.h"
-#include <iostream>
-#include <fstream>
-#include <iomanip>
-#include <ctime>
-#include <cmath>
-
-//#define DEBUG_RESULTS
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
- using std::shared_ptr;
- using std::make_shared;
- using std::static_pointer_cast;
-
- std::cout << std::endl << "==================== processor IMU test ======================" << std::endl;
-
- //load files containing accelerometer and gyroscope data
- std::ifstream data_file_acc;
- std::ifstream data_file_gyro;
- const char * filename_acc;
- const char * filename_gyro;
-
- //prepare creation of file if DEBUG_RESULTS activated
-#ifdef DEBUG_RESULTS
- std::ofstream debug_results;
- debug_results.open("debug_results.dat");
- if(debug_results)
- debug_results << "%%TimeStamp\t"
- << "dp_x\t" << "dp_y\t" << "dp_z\t" << "dq_x\t" << "dq_y\t" << "dq_z\t" << "dq_w\t" << "dv_x\t" << "dv_y\t" << "dv_z\t"
- << "Dp_x\t" << "Dp_y\t" << "Dp_z\t" << "Dq_x\t" << "Dq_y\t" << "Dq_z\t" << "Dq_w\t" << "Dv_x\t" << "Dv_y\t" << "Dv_z\t"
- << "X_x\t" << "X_y\t" << "X_z\t" << "Xq_x\t" << "Xq_y\t" << "Xq_z\t" << "Xq_w\t" << "Xv_x\t" << "Xv_y\t" << "Xv_z\t" << std::endl;
-#endif
-
- if (argc < 3)
- {
- std::cout << "Missing input argument! : needs 2 arguments (path to accelerometer file and path to gyroscope data)." << std::endl;
- }
- else
- {
- filename_acc = argv[1];
- filename_gyro = argv[2];
- data_file_acc.open(filename_acc);
- data_file_gyro.open(filename_gyro);
- std::cout << "Acc file: " << filename_acc << std::endl;
- std::cout << "Gyro file: " << filename_gyro << std::endl;
-
- std::string dummy;
- getline(data_file_acc, dummy); getline(data_file_gyro, dummy);
-
- if(!data_file_acc.is_open() || !data_file_gyro.is_open()){
- std::cerr << "Failed to open data files... Exiting" << std::endl;
- return 1;
- }
- }
-
- // Wolf problem
- ProblemPtr problem_ptr_ = Problem::create("PQVBB 3D");
- Eigen::VectorXs extrinsics(7);
- extrinsics << 0,0,0, 0,0,0,1; // IMU pose in the robot
- SensorBasePtr sensor_ptr = problem_ptr_->installSensor("IMU", "Main IMU", extrinsics, IntrinsicsBasePtr());
- problem_ptr_->installProcessor("IMU", "IMU pre-integrator", "Main IMU", "");
-
- // Time and data variables
- TimeStamp t;
- Scalar mti_clock, tmp;
- Eigen::Vector6s data;
- Eigen::Matrix6s data_cov;
- data_cov.setIdentity();
- data_cov.topLeftCorner(3,3) *= 0.01;
- data_cov.bottomRightCorner(3,3) *= 0.01;
-
- // Get initial data
- data_file_acc >> mti_clock >> data[0] >> data[1] >> data[2];
- data_file_gyro >> tmp >> data[3] >> data[4] >> data[5];
- t.set(mti_clock * 0.0001); // clock in 0,1 ms ticks
-
- // Set the origin
- Eigen::VectorXs x0(16);
- x0 << 0,0,0, 0,0,0,1, 0,0,0, 0,0,0, 0,0,0; // Try some non-zero biases
- problem_ptr_->getProcessorMotion()->setOrigin(x0, t);
-
- // Create one capture to store the IMU data arriving from (sensor / callback / file / etc.)
- CaptureIMUPtr imu_ptr = make_shared<CaptureIMU>(t, sensor_ptr, data, data_cov, Vector6s::Zero());
-
-// problem_ptr_->print();
-
- std::cout << "Main loop -----------" << std::endl;
-
- // main loop
- using namespace std;
- clock_t begin = clock();
- int n = 1;
- while(!data_file_acc.eof() && n < 5000){
- n++;
-
- // read new data
- data_file_acc >> mti_clock >> data[0] >> data[1] >> data[2];
- data_file_gyro >> tmp >> data[3] >> data[4] >> data[5];
- t.set(mti_clock * 0.0001); // clock in 0,1 ms ticks
-
-// data.setZero();
-// data(2) = 9.8;
-
- // assign data to capture
- imu_ptr->setData(data);
- imu_ptr->setTimeStamp(t);
-
- // process data in capture
- sensor_ptr->process(imu_ptr);
-
-#ifdef DEBUG_RESULTS
-
- // --- print to screen ----
-
- std::cout << "Current data : " << std::fixed << std::setprecision(3) << std::setw(8) << std::right
- << data.transpose() << std::endl;
-
- std::cout << "Current delta: " << std::fixed << std::setprecision(3) << std::setw(8) << std::right
- << problem_ptr_->getProcessorMotion()->getMotion().delta_.transpose() << std::endl;
-
- std::cout << "Integrated delta: " << std::fixed << std::setprecision(3) << std::setw(8)
- << problem_ptr_->getProcessorMotion()->getMotion().delta_integr_.transpose() << std::endl;
-
- Eigen::VectorXs x = problem_ptr_->getProcessorMotion()->getCurrentState();
-
- std::cout << "Integrated state: " << std::fixed << std::setprecision(3) << std::setw(8)
- << x.head(10).transpose() << std::endl;
-
- std::cout << "Integrated std : " << std::fixed << std::setprecision(3) << std::setw(8)
- << (problem_ptr_->getProcessorMotion()->getMotion().delta_integr_cov_.diagonal().transpose()).array().sqrt() << std::endl;
-
- std::cout << std::endl;
-
-//#ifdef DEBUG_RESULTS
- // ----- dump to file -----
-
- Eigen::VectorXs delta_debug;
- Eigen::VectorXs delta_integr_debug;
- Eigen::VectorXs x_debug;
- TimeStamp ts;
-
- delta_debug = problem_ptr_->getProcessorMotion()->getMotion().delta_;
- delta_integr_debug = problem_ptr_->getProcessorMotion()->getMotion().delta_integr_;
- x_debug = problem_ptr_->getProcessorMotion()->getCurrentState();
- ts = problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
-
- if(debug_results)
- debug_results << ts.get() << "\t" << delta_debug(0) << "\t" << delta_debug(1) << "\t" << delta_debug(2) << "\t" << delta_debug(3) << "\t" << delta_debug(4) << "\t"
- << delta_debug(5) << "\t" << delta_debug(6) << "\t" << delta_debug(7) << "\t" << delta_debug(8) << "\t" << delta_debug(9) << "\t"
- << delta_integr_debug(0) << "\t" << delta_integr_debug(1) << "\t" << delta_integr_debug(2) << "\t" << delta_integr_debug(3) << "\t" << delta_integr_debug(4) << "\t"
- << delta_integr_debug(5) << "\t" << delta_integr_debug(6) << "\t" << delta_integr_debug(7) << "\t" << delta_integr_debug(8) << "\t" << delta_integr_debug(9) << "\t"
- << x_debug(0) << "\t" << x_debug(1) << "\t" << x_debug(2) << "\t" << x_debug(3) << "\t" << x_debug(4) << "\t"
- << x_debug(5) << "\t" << x_debug(6) << "\t" << x_debug(7) << "\t" << x_debug(8) << "\t" << x_debug(9) << "\n";
-#endif
-
- }
- clock_t end = clock();
- double elapsed_secs = double(end - begin) / CLOCKS_PER_SEC;
-
- // Final state
- std::cout << "\nIntegration results ----------------------------------------------------------------------------------------------" << std::endl;
- std::cout << "Initial state: " << std::fixed << std::setprecision(3) << std::setw(8)
- << x0.head(16).transpose() << std::endl;
- std::cout << "Integrated delta: " << std::fixed << std::setprecision(3) << std::setw(8)
- << problem_ptr_->getProcessorMotion()->getMotion().delta_integr_.transpose() << std::endl;
- std::cout << "Integrated state: " << std::fixed << std::setprecision(3) << std::setw(8)
- << problem_ptr_->getProcessorMotion()->getCurrentState().head(16).transpose() << std::endl;
-// std::cout << "Integrated std : " << std::fixed << std::setprecision(3) << std::setw(8)
-// << (problem_ptr_->getProcessorMotion()->getMotion().delta_integr_cov_.diagonal().transpose()).array().sqrt() << std::endl;
-
- // Print statistics
- std::cout << "\nStatistics -----------------------------------------------------------------------------------" << std::endl;
- std::cout << "If you want meaningful CPU metrics, remove all couts in the loop / remove DEBUG_RESULTS definition variable, and compile in RELEASE mode!" << std::endl;
-
-#ifdef DEBUG_RESULTS
- std::cout << "\t\tWARNING : DEBUG_RESULTS ACTIVATED - slows the process (writing results to result_debugs.dat file)" << std::endl;
- debug_results.close();
-#endif
-
- TimeStamp t0, tf;
- t0 = problem_ptr_->getProcessorMotion()->getBuffer().get().front().ts_;
- tf = problem_ptr_->getProcessorMotion()->getBuffer().get().back().ts_;
- int N = problem_ptr_->getProcessorMotion()->getBuffer().get().size();
- std::cout << "t0 : " << t0.get() << " s" << std::endl;
- std::cout << "tf : " << tf.get() << " s" << std::endl;
- std::cout << "duration : " << tf-t0 << " s" << std::endl;
- std::cout << "N samples : " << N << std::endl;
- std::cout << "frequency : " << (N-1)/(tf-t0) << " Hz" << std::endl;
- std::cout << "CPU time : " << elapsed_secs << " s" << std::endl;
- std::cout << "s/integr : " << elapsed_secs/(N-1)*1e6 << " us" << std::endl;
- std::cout << "integr/s : " << (N-1)/elapsed_secs << " ips" << std::endl;
-
- // close data files
- data_file_acc.close(); // no impact on leaks
- data_file_gyro.close();
-
- return 0;
-}
diff --git a/demos/demo_processor_imu_jacobians.cpp b/demos/demo_processor_imu_jacobians.cpp
deleted file mode 100644
index 22c797d6d..000000000
--- a/demos/demo_processor_imu_jacobians.cpp
+++ /dev/null
@@ -1,418 +0,0 @@
-/**
- * \file test_processor_imu_jacobians.cpp
- *
- * Created on: Sep 26, 2016
- * \author: AtDinesh
- */
-
-//Wolf
-#include "base/capture/capture_IMU.h"
-#include "base/sensor/sensor_IMU.h"
-#include <test/processor_IMU_UnitTester.h>
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/state_block/state_block.h"
-#include "base/state_block/state_quaternion.h"
-#include <iostream>
-#include <fstream>
-#include <iomanip>
-#include <ctime>
-#include <cmath>
-
-//#define DEBUG_RESULTS
-
-using namespace wolf;
-
-void remapJacDeltas_quat0(IMU_jac_deltas& _jac_delta, Eigen::Map<Eigen::Quaternions>& _Dq0, Eigen::Map<Eigen::Quaternions>& _dq0);
-void remapJacDeltas_quat(IMU_jac_deltas& _jac_delta, Eigen::Map<Eigen::Quaternions>& _Dq, Eigen::Map<Eigen::Quaternions>& _dq, const int& place );
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- std::cout << std::endl << "==================== processor IMU : Checking Jacobians ======================" << std::endl;
-
- TimeStamp t;
- Eigen::Vector6s data_;
- wolf::Scalar deg_to_rad = 3.14159265359/180.0;
- data_ << 10,0.5,3, 100*deg_to_rad,110*deg_to_rad,30*deg_to_rad;
-
- // Wolf problem
- ProblemPtr wolf_problem_ptr_ = Problem::create("PQVBB 3D");
- Eigen::VectorXs IMU_extrinsics(7);
- IMU_extrinsics << 0,0,0, 0,0,0,1; // IMU pose in the robot
- //SensorBase* sensor_ptr = wolf_problem_ptr_->installSensor("IMU", "Main IMU", IMU_extrinsics, nullptr);
- //wolf_problem_ptr_->installProcessor("IMU", "IMU pre-integrator", "Main IMU", "");
-
- // Set the origin
- t.set(0.0001); // clock in 0,1 ms ticks
- Eigen::VectorXs x0(16);
- x0 << 0,1,0, 0,0,0,1, 1,0,0, 0,0,.000, 0,0,.000; // P Q V B B
-
- //wolf_problem_ptr_->getProcessorMotion()->setOrigin(x0, t);
-
- //CaptureIMU* imu_ptr;
-
- ProcessorIMU_UnitTester processor_imu;
- //processor_imu.setOrigin(x0, t);
- wolf::Scalar ddelta_bias = 0.00000001;
- wolf::Scalar dt = 0.001;
-
- //defining a random Delta to begin with (not to use Origin point)
- Eigen::Matrix<wolf::Scalar,10,1> Delta0;
- Delta0 = Eigen::Matrix<wolf::Scalar,10,1>::Random();
- Delta0.head<3>() = Delta0.head<3>()*100;
- Delta0.tail<3>() = Delta0.tail<3>()*10;
- Eigen::Vector3s ang0, ang;
- ang0 << 120.08*deg_to_rad, 12.36*deg_to_rad, 54.32*deg_to_rad;
- //Delta0 << 0,0,0, 0,0,0,1, 0,0,0;
- Eigen::Map<Eigen::Quaternions> Delta0_quat(Delta0.data()+3);
- Delta0_quat = v2q(ang0);
- Delta0_quat.normalize();
- ang = q2v(Delta0_quat);
-
- std::cout << "\ninput Delta0 : " << Delta0 << std::endl;
- std::cout << "\n rotation vector we start with :\n" << ang << std::endl;
-
- struct IMU_jac_bias bias_jac = processor_imu.finite_diff_ab(dt, data_, ddelta_bias, Delta0);
-
- Eigen::Map<Eigen::Quaternions> Dq0(NULL);
- Eigen::Map<Eigen::Quaternions> dq0(NULL);
- Eigen::Map<Eigen::Quaternions> Dq_noisy(NULL);
- Eigen::Map<Eigen::Quaternions> dq_noisy(NULL);
- Eigen::Map<Eigen::Quaternions> q_in_1(NULL), q_in_2(NULL);
-
- /* IMU_jac_deltas struct form :
- contains vectors of size 7 :
- Elements at place 0 are those not affected by the bias noise that we add (da_bx,..., dw_bx,... ).
- place 1 : added da_bx in data place 2 : added da_by in data place 3 : added da_bz in data
- place 4 : added dw_bx in data place 5 : added dw_by in data place 6 : added dw_bz in data
- */
-
- Eigen::Matrix3s dDp_dab, dDv_dab, dDp_dwb, dDv_dwb, dDq_dab, dDq_dwb;
-
- /*
- dDp_dab = [dDp_dab_x, dDp_dab_y, dDp_dab_z]
- dDp_dab_x = (dDp(ab_x + dab_x, ab_y, ab_z) - dDp(ab_x,ab_y,ab_z)) / dab_x
- dDp_dab_x = (dDp(ab_x, ab_y + dab_y, ab_z) - dDp(ab_x,ab_y,ab_z)) / dab_y
- dDp_dab_x = (dDp(ab_x, ab_y, ab_z + dab_z) - dDp(ab_x,ab_y,ab_z)) / dab_z
-
- similar for dDv_dab
- note dDp_dab_x, dDp_dab_y, dDp_dab_z, dDv_dab_x, dDv_dab_y, dDv_dab_z are 3x1 vectors !
-
- dDq_dab = 0_{3x3}
- dDq_dwb = [dDq_dwb_x, dDq_dwb_y, dDq_dwb_z]
- dDq_dwb_x = log( dR(wb).transpose() * dR(wb - dwb_x))/dwb_x
- = log( dR(wb).transpose() * exp((wx - wbx - dwb_x)dt, (wy - wby)dt, (wy - wby)dt))/dwb_x
- dDq_dwb_y = log( dR(wb).transpose() * dR(wb - dwb_y))/dwb_y
- dDq_dwb_z = log( dR(wb).transpose() * dR(wb + dwb_z))/dwb_z
-
- Note : dDq_dwb must be computed recursively ! So comparing the one returned by processor_imu and the numerical
- one will have no sense if we aredoing this from a random Delta. The Delta here should be the origin.
- dDq_dwb_ = dR.tr()*dDq_dwb - Jr(wdt)*dt
- Then at first step, dR.tr() = Id, dDq_dwb = 0_{3x3}, which boils down to dDq_dwb_ = Jr(wdt)*dt
- */
-
- std::cout << "\n input data : \n" << data_ << std::endl;
-
- new (&q_in_1) Eigen::Map<Eigen::Quaternions>(bias_jac.Delta0_.data() + 3);
- for(int i=0;i<3;i++){
- dDp_dab.block<3,1>(0,i) = (bias_jac.Deltas_noisy_vect_(i).head(3) - bias_jac.Delta0_.head(3))/ddelta_bias;
- dDv_dab.block<3,1>(0,i) = (bias_jac.Deltas_noisy_vect_(i).tail(3) - bias_jac.Delta0_.tail(3))/ddelta_bias;
-
- dDp_dwb.block<3,1>(0,i) = (bias_jac.Deltas_noisy_vect_(i+3).head(3) - bias_jac.Delta0_.head(3))/ddelta_bias;
- dDv_dwb.block<3,1>(0,i) = (bias_jac.Deltas_noisy_vect_(i+3).tail(3) - bias_jac.Delta0_.tail(3))/ddelta_bias;
-
- new (&q_in_2) Eigen::Map<Eigen::Quaternions>(bias_jac.Deltas_noisy_vect_(i).data() + 3);
- dDq_dab.block<3,1>(0,i) = R2v( q_in_1.matrix().transpose() * q_in_2.matrix())/ddelta_bias;
-
- new (&q_in_2) Eigen::Map<Eigen::Quaternions>(bias_jac.Deltas_noisy_vect_(i+3).data() + 3);
- dDq_dwb.block<3,1>(0,i) = R2v( q_in_1.matrix().transpose() * q_in_2.matrix())/ddelta_bias;
- //std::cout << "matrix operation result :" << i << "\n" << q_in_1.matrix().transpose() * q_in_2.matrix() << std::endl;
- //std::cout << "matrix operation result to vector :" << i << "\n" << R2v( q_in_1.matrix().transpose() * q_in_2.matrix()) << std::endl;
- }
-/* Delta1 = bias_jac.Deltas_noisy_vect_(3);
- Delta2 = bias_jac.Deltas_noisy_vect_(4);
- Delta3 = bias_jac.Deltas_noisy_vect_(5);
-
- if( (Delta1 == Delta2 || Delta1 == Delta3 ))
- std::cout << "\n problem" << std::endl;
- else
- std::cout << "\n no problem" << std::endl;
- if(Delta2 == Delta3)
- std::cout << "\n problem" << std::endl;
- else
- std::cout << "\n no problem" << std::endl;*/
-
- //Check the jacobians wrt to bias using finite difference
-
- if(dDp_dab.isApprox(bias_jac.dDp_dab_, wolf::Constants::EPS) )
- std::cout<< "dDp_dab_ jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDp_dab_ jacobian is not correct ..." << std::endl;
- std::cout << "dDp_dab : \n" << dDp_dab << "\n bias_jac.dDp_dab_ :\n" << bias_jac.dDp_dab_ << "\n" << std::endl;
- std::cout << "dDp_dab_a - dDp_dab_ : \n" << bias_jac.dDp_dab_ - dDp_dab << "\n" << std::endl;
- }
-
- if(dDv_dab.isApprox(bias_jac.dDv_dab_, wolf::Constants::EPS) )
- std::cout<< "dDv_dab_ jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDv_dab_ jacobian is not correct ..." << std::endl;
- std::cout << "dDv_dab_ : \n" << dDv_dab << "\n bias_jac.dDv_dab_ :\n" << bias_jac.dDv_dab_ << "\n" << std::endl;
- std::cout << "dDv_dab_a - dDv_dab_ : \n" << bias_jac.dDv_dab_ - dDv_dab << "\n" << std::endl;
- }
-
- if(dDp_dwb.isApprox(bias_jac.dDp_dwb_, wolf::Constants::EPS) )
- std::cout<< "dDp_dwb_ jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDp_dwb_ jacobian is not correct ..." << std::endl;
- std::cout << "dDp_dwb_ : \n" << dDp_dwb << "\n bias_jac.dDp_dwb_ :\n" << bias_jac.dDp_dwb_ << "\n" << std::endl;
- std::cout << "dDp_dwb_a - dDp_dwb_ : \n" << bias_jac.dDp_dwb_ - dDp_dwb << "\n" << std::endl;
- }
-
- if(dDv_dwb.isApprox(bias_jac.dDv_dwb_, wolf::Constants::EPS) )
- std::cout<< "dDv_dwb_ jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDv_dwb_ jacobian is not correct ..." << std::endl;
- std::cout << "dDv_dwb_ : \n" << dDv_dwb << "\n bias_jac.dDv_dwb_ :\n" << bias_jac.dDv_dwb_ << "\n" << std::endl;
- std::cout << "dDv_dwb_a - dDv_dwb_ : \n" << bias_jac.dDv_dwb_ - dDv_dwb << "\n" << std::endl;
- }
-
- if(dDq_dwb.isApprox(bias_jac.dDq_dwb_, wolf::Constants::EPS) )
- std::cout<< "dDq_dwb_ jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDq_dwb_ jacobian is not correct ..." << std::endl;
- std::cout << "dDq_dwb_ : \n" << dDq_dwb << "\n bias_jac.dDq_dwb_ :\n" << bias_jac.dDq_dwb_ << "\n" << std::endl;
- std::cout << "dDq_dwb_a - dDq_dwb_ : \n" << bias_jac.dDq_dwb_ - dDq_dwb << "\n" << std::endl;
- }
-
- //Check jacobians that are supposed to be Zeros just in case
- if(dDq_dab.isZero(wolf::Constants::EPS))
- std::cout<< "dDq_dab_ jacobian is correct (Zero) !" << std::endl;
- else
- std::cout<< "\t\tdDq_dab_ jacobian is not Zero :" << dDq_dab << std::endl;
-
- /* Numerical method to check jacobians wrt noise
-
- dDp_dP = [dDp_dPx, dDp_dPy, dDp_dPz]
- dDp_dPx = ((P + dPx) - P)/dPx = Id
- dDp_dPy = ((P + dPy) - P)/dPy = Id
- dDp_dPz = ((P + dPz) - P)/dPz = Id
-
- dDp_dV = [dDp_dVx, dDp_dVy, dDp_dVz]
- dDp_dVx = ((V + dVx)*dt - V*dt)/dVx = Id*dt
- dDp_dVy = ((V + dVy)*dt - V*dt)/dVy = Id*dt
- dDp_dVz = ((V + dVz)*dt - V*dt)/dVz = Id*dt
-
- dDp_dO = [dDp_dOx, dDp_dOy, dDp_dOz]
- dDp_dOx = (( dR(Theta + dThetax)*dp ) - ( dR(Theta)*dp ))/dThetax
- = (( dR(Theta) * exp(dThetax,0,0)*dp ) - ( dR(Theta)*dp ))/dThetax
- dDp_dOy = (( dR(Theta) * exp(0,dThetay,0)*dp ) - ( dR(Theta)*dp ))/dThetay
- dDp_dOz = (( dR(Theta) * exp(0,0,dThetaz)*dp ) - ( dR(Theta)*dp ))/dThetaz
-
- dDv_dP = [dDv_dPx, dDv_dPy, dDv_dPz] = [0, 0, 0]
-
- dDv_dV = [dDv_dVx, dDv_dVy, dDv_dVz]
- dDv_dVx = ((V + dVx) - V)/dVx = Id
- dDv_dVy = ((V + dVy) - V)/dVy = Id
- dDv_dVz = ((V + dVz) - V)/dVz = Id
-
- dDv_dO = [dDv_dOx, dDv_dOy, dDv_dOz]
- dDv_dOx = (( dR(Theta + dThetax)*dv ) - ( dR(Theta)*dv ))/dThetax
- = (( dR(Theta) * exp(dThetax,0,0)*dv ) - ( dR(Theta)*dv ))/dThetax
- dDv_dOx = (( dR(Theta) * exp(0,dThetay,0)*dv ) - ( dR(Theta)*dv ))/dThetay
- dDv_dOz = (( dR(Theta) * exp(0,0,dThetaz)*dv ) - ( dR(Theta)*dv ))/dThetaz
-
- dDp_dp = [dDp_dpx, dDp_dpy, dDp_dpz]
- dDp_dpx = ( dR*(p + dpx) - dR*(p))/dpx
- dDp_dpy = ( dR*(p + dpy) - dR*(p))/dpy
- dDp_dpz = ( dR*(p + dpz) - dR*(p))/dpy
-
- dDp_dv = [dDp_dvx, dDp_dvy, dDp_dvz] = [0, 0, 0]
-
- dDp_do = [dDp_dox, dDp_doy, dDp_doz] = [0, 0, 0]
-
- dDv_dp = [dDv_dpx, dDv_dpy, dDv_dpz] = [0, 0, 0]
-
- dDv_dv = [dDv_dvx, dDv_dvy, dDv_dvz]
- dDv_dvx = ( dR*(v + dvx) - dR*(v))/dvx
- dDv_dvy = ( dR*(v + dvy) - dR*(v))/dvy
- dDv_dvz = ( dR*(v + dvz) - dR*(v))/dvz
-
- dDv_do = [dDv_dox, dDv_doy, dDv_doz] = [0, 0, 0]
-
- dDo_dp = dDo_dv = dDo_dP = dDo_dV = [0, 0, 0]
-
- dDo_dO = [dDo_dOx, dDo_dOy, dDo_dOz]
-
- dDo_dOx = log( (dR(Theta) * dr(theta)).transpose() * dR(Theta+dThetax) * dr(theta) )/dThetax
- = log( (dR(Theta) * dr(theta)).transpose() * (dR(Theta)*exp(dThetax,0,0)) * dr(theta) )/dThetax
- = log( (_Delta * _delta).transpose() * (_Delta_noisy * _delta))
- dDo_dOy = log( (dR(Theta) * dr(theta)).transpose() * (dR(Theta)*exp(0,dThetay,0)) * dr(theta) )/dThetay
- dDo_dOz = log( (dR(Theta) * dr(theta)).transpose() * (dR(Theta)*exp(0,0,dThetaz)) * dr(theta) )/dThetaz
-
- dDo_do = [dDo_dox, dDo_doy, dDo_doz]
-
- dDo_dox = log( (dR(Theta) * dr(theta)).transpose() * dR(Theta) * dr(theta+dthetax) )/dthetax
- = log( (dR(Theta) * dr(theta)).transpose() * dR(Theta) * (dr(theta)*exp(dthetax,0,0)) )/dthetax
- = log( (_Delta * _delta).transpose() * (_Delta * _delta_noisy))
- dDo_doy = log( (dR(Theta) * dr(theta)).transpose() * dR(Theta) * (dr(theta)*exp(0,dthetay,0)) )/dthetay
- dDo_doz = log( (dR(Theta) * dr(theta)).transpose() * dR(Theta) * (dr(theta)*exp(0,0,dthetaz)) )/dthetaz
- */
-
- //taking care of noise now
- Eigen::Matrix<wolf::Scalar,9,1> Delta_noise;
- Eigen::Matrix<wolf::Scalar,9,1> delta_noise;
-
- Delta_noise << 0.00000001, 0.00000001, 0.00000001, 0.0001, 0.0001, 0.0001, 0.00000001, 0.00000001, 0.00000001;
- delta_noise << 0.00000001, 0.00000001, 0.00000001, 0.0001, 0.0001, 0.0001, 0.00000001, 0.00000001, 0.00000001;
-
- struct IMU_jac_deltas deltas_jac = processor_imu.finite_diff_noise(dt, data_, Delta_noise, delta_noise, Delta0);
-
- /* reminder :
- jacobian_delta_preint_vect_ jacobian_delta_vect_
- 0: + 0, 0: + 0
- 1: +dPx, 2: +dPy, 3: +dPz 1: + dpx, 2: +dpy, 3: +dpz
- 4: +dOx, 5: +dOy, 6: +dOz 4: + dox, 5: +doy, 6: +doz
- 7: +dVx, 8: +dVy, 9: +dVz 7: + dvx, 8: +dvy, 9: +dvz
- */
-
- Eigen::Matrix3s dDp_dP, dDp_dV, dDp_dO, dDv_dP, dDv_dV, dDv_dO, dDo_dP, dDo_dV, dDo_dO;
- Eigen::Matrix3s dDp_dp, dDp_dv, dDp_do, dDv_dp, dDv_dv, dDv_do, dDo_dp, dDo_dv, dDo_do;
-
- remapJacDeltas_quat0(deltas_jac, Dq0, dq0);
-
- for(int i = 0; i < 3; i++){
-
- //dDp_dPx = ((P + dPx) - P)/dPx
- dDp_dP.block<3,1>(0,i) = (deltas_jac.Delta_noisy_vect_(i).head(3) - deltas_jac.Delta0_.head(3))/Delta_noise(i);
- //Dp_dVx = ((V + dVx)*dt - V*dt)/dVx
- dDp_dV.block<3,1>(0,i) = (deltas_jac.Delta_noisy_vect_(i+6).tail(3)*dt - deltas_jac.Delta0_.tail(3)*dt)/Delta_noise(i+6);
- //dDp_dOx = (( dR(Theta) * exp(dThetax,0,0)*dp ) - ( dR(Theta)*dp ))/dThetax
- remapJacDeltas_quat(deltas_jac, Dq_noisy, dq_noisy, i+3);
- dDp_dO.block<3,1>(0,i) = ((Dq_noisy.matrix() * deltas_jac.delta0_.head(3)) - (Dq0.matrix()* deltas_jac.delta0_.head(3)))/Delta_noise(i+3);
-
- //dDv_dP = [0, 0, 0]
- //dDv_dVx = ((V + dVx) - V)/dVx
- dDv_dV.block<3,1>(0,i) = (deltas_jac.Delta_noisy_vect_(i+6).tail(3) - deltas_jac.Delta0_.tail(3))/Delta_noise(i+6);
- //dDv_dOx = (( dR(Theta) * exp(dThetax,0,0)*dv ) - ( dR(Theta)*dv ))/dThetax
- dDv_dO.block<3,1>(0,i) = ((Dq_noisy.matrix() * deltas_jac.delta0_.tail(3)) - (Dq0.matrix()* deltas_jac.delta0_.tail(3)))/Delta_noise(i+3);
-
- //dDo_dP = dDo_dV = [0, 0, 0]
- //dDo_dOx = log( (dR(Theta) * dr(theta)).transpose() * (dR(Theta)*exp(dThetax,0,0)) * dr(theta) )/dThetax
- dDo_dO.block<3,1>(0,i) = R2v( (Dq0.matrix() * dq0.matrix()).transpose() * (Dq_noisy.matrix() * dq0.matrix()) )/Delta_noise(i+3);
-
- //dDp_dpx = ( dR*(p + dpx) - dR*(p))/dpx
- dDp_dp.block<3,1>(0,i) = ( (Dq0.matrix() * deltas_jac.delta_noisy_vect_(i).head(3)) - (Dq0.matrix() * deltas_jac.delta0_.head(3)) )/delta_noise(i);
- //dDp_dv = dDp_do = [0, 0, 0]
-
- //dDv_dp = [0, 0, 0]
- //dDv_dvx = ( dR*(v + dvx) - dR*(v))/dvx
- dDv_dv.block<3,1>(0,i) = ( (Dq0 * deltas_jac.delta_noisy_vect_(i+6).tail(3)) - (Dq0 * deltas_jac.delta0_.tail(3)) )/delta_noise(i+6);
- //dDv_do = [0, 0, 0]
-
- //dDo_dp = dDo_dv = [0, 0, 0]
- //dDo_dox = log( (dR(Theta) * dr(theta)).transpose() * dR(Theta) * (dr(theta)*exp(dthetax,0,0)) )/dthetax
- dDo_do.block<3,1>(0,i) = R2v( (Dq0.matrix() * dq0.matrix()).transpose() * (Dq0.matrix() * dq_noisy.matrix()) )/Delta_noise(i+3);
- }
-
- /* jacobians wrt deltas have PVQ form :
- dDp_dP = deltas_jac.jacobian_delta_preint_.block(0,0,3,3); dDp_dV = deltas_jac.jacobian_delta_preint_.block(0,3,3,3); dDp_dO = deltas_jac.jacobian_delta_preint_.block(0,6,3,3);
- dDv_dP = deltas_jac.jacobian_delta_preint_.block(3,0,3,3); dDv_dV = deltas_jac.jacobian_delta_preint_.block(3,3,3,3); dDv_dO = deltas_jac.jacobian_delta_preint_.block(3,6,3,3);
- dDo_dP = deltas_jac.jacobian_delta_preint_.block(6,0,3,3); dDo_dV = deltas_jac.jacobian_delta_preint_.block(6,3,3,3); dDo_dO = deltas_jac.jacobian_delta_preint_.block(6,6,3,3);
- */
-
- if(dDp_dP.isApprox(deltas_jac.jacobian_delta_preint_.block(0,0,3,3), wolf::Constants::EPS) )
- std::cout<< "dDp_dP jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDp_dP jacobian is not correct ..." << std::endl;
- std::cout << "dDp_dP : \n" << dDp_dP << "\n deltas_jac.jacobian_delta_preint_.block(0,0,3,3) :\n" << deltas_jac.jacobian_delta_preint_.block(0,0,3,3) << "\n" << std::endl;
- std::cout << "dDp_dP_a - dDp_dP : \n" << deltas_jac.jacobian_delta_preint_.block(0,0,3,3) - dDp_dP << "\n" << std::endl;
- }
-
- if(dDp_dV.isApprox(deltas_jac.jacobian_delta_preint_.block(0,6,3,3), wolf::Constants::EPS) )
- std::cout<< "dDp_dV jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDp_dV jacobian is not correct ..." << std::endl;
- std::cout << "dDp_dV : \n" << dDp_dV << "\n deltas_jac.jacobian_delta_preint_.block(0,6,3,3) :\n" << deltas_jac.jacobian_delta_preint_.block(0,6,3,3) << "\n" << std::endl;
- std::cout << "dDp_dV_a - dDp_dV : \n" << deltas_jac.jacobian_delta_preint_.block(0,6,3,3) - dDp_dV << "\n" << std::endl;
- }
-
- if(dDp_dO.isApprox(deltas_jac.jacobian_delta_preint_.block(0,3,3,3), wolf::Constants::EPS) )
- std::cout<< "dDp_dO jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDp_dO jacobian is not correct ..." << std::endl;
- std::cout << "dDp_dO : \n" << dDp_dO << "\n deltas_jac.jacobian_delta_preint_.block(0,3,3,3) :\n" << deltas_jac.jacobian_delta_preint_.block(0,3,3,3) << "\n" << std::endl;
- std::cout << "dDp_dO_a - dDp_dO : \n" << deltas_jac.jacobian_delta_preint_.block(0,3,3,3) - dDp_dO << "\n" << std::endl;
- }
-
- if(dDv_dV.isApprox(deltas_jac.jacobian_delta_preint_.block(6,6,3,3), wolf::Constants::EPS) )
- std::cout<< "dDv_dV jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDv_dV jacobian is not correct ..." << std::endl;
- std::cout << "dDv_dV : \n" << dDv_dV << "\n deltas_jac.jacobian_delta_preint_.block(6,6,3,3) :\n" << deltas_jac.jacobian_delta_preint_.block(6,6,3,3) << "\n" << std::endl;
- std::cout << "dDv_dV_a - dDv_dV : \n" << deltas_jac.jacobian_delta_preint_.block(6,6,3,3) - dDv_dV << "\n" << std::endl;
- }
-
- if(dDv_dO.isApprox(deltas_jac.jacobian_delta_preint_.block(6,3,3,3), wolf::Constants::EPS) )
- std::cout<< "dDv_dO jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDv_dO jacobian is not correct ..." << std::endl;
- std::cout << "dDv_dO : \n" << dDv_dO << "\n deltas_jac.jacobian_delta_preint_.block(6,3,3,3) :\n" << deltas_jac.jacobian_delta_preint_.block(6,3,3,3) << "\n" << std::endl;
- std::cout << "dDv_dO_a - dDv_dO : \n" << deltas_jac.jacobian_delta_preint_.block(6,3,3,3) - dDv_dO << "\n" << std::endl;
- }
-
- if(dDo_dO.isApprox(deltas_jac.jacobian_delta_preint_.block(3,3,3,3), wolf::Constants::EPS) )
- std::cout<< "dDo_dO jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDo_dO jacobian is not correct ..." << std::endl;
- std::cout << "dDo_dO : \n" << dDo_dO << "\n deltas_jac.jacobian_delta_preint_.block(3,3,3,3) :\n" << deltas_jac.jacobian_delta_preint_.block(3,3,3,3) << "\n" << std::endl;
- std::cout << "dDo_dO_a - dDo_dO : \n" << deltas_jac.jacobian_delta_preint_.block(3,3,3,3) - dDo_dO << "\n" << std::endl;
- }
-
- Eigen::Matrix3s dDp_dp_a, dDv_dv_a, dDo_do_a;
- dDp_dp_a = deltas_jac.jacobian_delta_.block(0,0,3,3);
- dDv_dv_a = deltas_jac.jacobian_delta_.block(6,6,3,3);
- dDo_do_a = deltas_jac.jacobian_delta_.block(3,3,3,3);
-
- if(dDp_dp.isApprox(dDp_dp_a, wolf::Constants::EPS) )
- std::cout<< "dDp_dp jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDp_dp jacobian is not correct ..." << std::endl;
- std::cout << "dDp_dp : \n" << dDv_dp << "\n dDp_dp_a :\n" << dDp_dp_a << "\n" << std::endl;
- std::cout << "dDp_dp_a - dDp_dp : \n" << dDp_dp_a - dDv_dp << "\n" << std::endl;
- }
-
- if(dDv_dv.isApprox(dDv_dv_a, wolf::Constants::EPS) )
- std::cout<< "dDv_dv jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDv_dv jacobian is not correct ..." << std::endl;
- std::cout << "dDv_dv : \n" << dDv_dv << "\n dDv_dv_a :\n" << dDv_dv_a << "\n" << std::endl;
- std::cout << "dDv_dv_a - dDv_dv : \n" << dDv_dv_a - dDv_dv << "\n" << std::endl;
- }
-
- if(dDo_do.isApprox(dDo_do_a, wolf::Constants::EPS) )
- std::cout<< "dDo_do jacobian is correct !" << std::endl;
- else{
- std::cout<< "\t\tdDo_do jacobian is not correct ..." << std::endl;
- std::cout << "dDo_do : \n" << dDo_do << "\n dDo_do_a :\n" << dDo_do_a << "\n" << std::endl;
- std::cout << "dDo_do_a - dDo_do : \n" << dDo_do_a - dDo_do << "\n" << std::endl;
- }
-
- return 0;
-}
-
-using namespace wolf;
-
-void remapJacDeltas_quat0(IMU_jac_deltas& _jac_delta, Eigen::Map<Eigen::Quaternions>& _Dq0, Eigen::Map<Eigen::Quaternions>& _dq0){
-
- new (&_Dq0) Eigen::Map<const Eigen::Quaternions>(_jac_delta.Delta0_.data() + 3);
- new (&_dq0) Eigen::Map<const Eigen::Quaternions>(_jac_delta.delta0_.data() + 3);
-}
-
-void remapJacDeltas_quat(IMU_jac_deltas& _jac_delta, Eigen::Map<Eigen::Quaternions>& _Dq, Eigen::Map<Eigen::Quaternions>& _dq, const int& place ){
-
- assert(place < _jac_delta.Delta_noisy_vect_.size());
- new (&_Dq) Eigen::Map<const Eigen::Quaternions>(_jac_delta.Delta_noisy_vect_(place).data() + 3);
- new (&_dq) Eigen::Map<const Eigen::Quaternions>(_jac_delta.delta_noisy_vect_(place).data() + 3);
-}
diff --git a/demos/demo_processor_odom_3D.cpp b/demos/demo_processor_odom_3D.cpp
deleted file mode 100644
index 2427dc24b..000000000
--- a/demos/demo_processor_odom_3D.cpp
+++ /dev/null
@@ -1,100 +0,0 @@
-/**
- * \file test_processor_odom_3D.cpp
- *
- * Created on: Oct 7, 2016
- * \author: jsola
- */
-
-#include "base/capture/capture_IMU.h"
-#include "base/problem/problem.h"
-#include "base/sensor/sensor_odom_2D.h"
-#include "base/processor/processor_odom_3D.h"
-#include "base/map/map_base.h"
-#include "base/landmark/landmark_base.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-
-#include <cstdlib>
-
-using namespace wolf;
-using std::cout;
-using std::endl;
-using Eigen::Vector3s;
-using Eigen::Vector6s;
-using Eigen::Vector7s;
-using Eigen::Quaternions;
-using Eigen::VectorXs;
-
-int main (int argc, char** argv)
-{
- cout << "\n========= Test ProcessorOdom3D ===========" << endl;
-
- std::string wolf_root = _WOLF_ROOT_DIR;
-
- TimeStamp tf;
- if (argc == 1)
- tf = 1.0;
- else
- {
-
- tf.set(strtod(argv[1],nullptr));
- }
- cout << "Final timestamp tf = " << tf.get() << " s" << endl;
-
- ProblemPtr problem = Problem::create("PO", 3);
- ceres::Solver::Options ceres_options;
-// ceres_options.max_num_iterations = 1000;
-// ceres_options.function_tolerance = 1e-10;
-// ceres_options.gradient_check_relative_precision = 1e-10;
-// ceres_options.gradient_tolerance = 1e-10;
- ceres_options.minimizer_progress_to_stdout = true;
- CeresManager ceres_manager(problem, ceres_options);
-
- SensorBasePtr sen = problem->installSensor("ODOM 3D", "odom", (Vector7s()<<0,0,0,0,0,0,1).finished(), wolf_root + "/src/examples/sensor_odom_3D.yaml");
- ProcessorParamsOdom3DPtr proc_params = std::make_shared<ProcessorParamsOdom3D>();
- problem->installProcessor("ODOM 3D", "odometry integrator", sen, proc_params);
-
- // Time and prior
- Scalar dt = 0.1;
-
- problem->setPrior((Vector7s()<<0,0,0,0,0,0,1).finished(), Matrix6s::Identity() * 1e-8, TimeStamp(0), dt/2);
-
- // Motion data
- Scalar dx = .1;
- Scalar dyaw = 2*M_PI/5;
- Vector6s data((Vector6s() << dx*cos(dyaw/2),dx*sin(dyaw/2),0,0,0,dyaw).finished()); // will integrate this data repeatedly
-
- CaptureMotionPtr cap_odo = std::make_shared<CaptureMotion>("ODOM 3D", TimeStamp(0), sen, data, 7, 6, nullptr);
-
- cout << "t: " << std::setprecision(2) << 0 << " \t x = ( " << problem->getCurrentState().transpose() << ")" << endl;
-
- for (TimeStamp t = dt; t < tf+dt/2; t += dt)
- {
- cap_odo->setTimeStamp(t);
- cap_odo->setData(data);
-
- sen->process(cap_odo);
-
- cout << "t: " << std::setprecision(2) << t.get() << " \t x = ( " << problem->getCurrentState().transpose() << ")" << endl;
-
-// ceres::Solver::Summary summary = ceres_manager.solve();
-
-// ceres_manager.computeCovariances(ALL);
-
-// cout << summary.BriefReport() << endl;
-
- }
-
- problem->print(1,0,1,0);
-// for (auto frm : problem->getTrajectory()->getFrameList())
-// {
-// frm->setState(problem->zeroState());
-// }
-// problem->print(1,0,1,0);
- std::string brief_report = ceres_manager.solve(SolverManager::ReportVerbosity::FULL);
- std::cout << brief_report << std::endl;
- problem->print(1,0,1,0);
-
- problem.reset();
-
- return 0;
-}
diff --git a/demos/demo_processor_tracker_feature.cpp b/demos/demo_processor_tracker_feature.cpp
deleted file mode 100644
index eccd7b49e..000000000
--- a/demos/demo_processor_tracker_feature.cpp
+++ /dev/null
@@ -1,57 +0,0 @@
-/**
- * \file test_processor_tracker_feature.cpp
- *
- * Created on: Apr 11, 2016
- * \author: jvallve
- */
-
-//std
-#include <iostream>
-
-//Wolf
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/sensor/sensor_base.h"
-#include "base/state_block/state_block.h"
-#include "base/processor/processor_tracker_feature_dummy.h"
-#include "base/capture/capture_void.h"
-
-int main()
-{
- using namespace wolf;
- using std::shared_ptr;
- using std::make_shared;
- using std::static_pointer_cast;
-
- std::cout << std::endl << "==================== processor tracker feature test ======================" << std::endl;
-
- // Wolf problem
- ProblemPtr wolf_problem_ptr_ = Problem::create("PO", 2);
- SensorBasePtr sensor_ptr_ = make_shared<SensorBase>("ODOM 2D", std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)),
- std::make_shared<StateBlock>(Eigen::VectorXs::Zero(1)),
- std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), 2);
-
- ProcessorParamsTrackerFeaturePtr params_trk = std::make_shared<ProcessorParamsTrackerFeature>();
- params_trk->max_new_features = 4;
- params_trk->min_features_for_keyframe = 7;
- params_trk->time_tolerance = 0.25;
- shared_ptr<ProcessorTrackerFeatureDummy> processor_ptr_ = make_shared<ProcessorTrackerFeatureDummy>(params_trk);
-
- wolf_problem_ptr_->addSensor(sensor_ptr_);
- sensor_ptr_->addProcessor(processor_ptr_);
-
- std::cout << "sensor & processor created and added to wolf problem" << std::endl;
-
- TimeStamp t(0);
- Scalar dt = 0.5;
- for (auto i = 0; i < 10; i++)
- {
- processor_ptr_->process(make_shared<CaptureVoid>(t, sensor_ptr_));
- t += dt;
- }
-
- wolf_problem_ptr_->print(2);
-
- return 0;
-}
-
diff --git a/demos/demo_processor_tracker_landmark.cpp b/demos/demo_processor_tracker_landmark.cpp
deleted file mode 100644
index b3ce8be59..000000000
--- a/demos/demo_processor_tracker_landmark.cpp
+++ /dev/null
@@ -1,95 +0,0 @@
-/**
- * \file test_processor_tracker_landmark.cpp
- *
- * Created on: Apr 12, 2016
- * \author: jvallve
- */
-
-//std
-#include <iostream>
-
-//Wolf
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/sensor/sensor_base.h"
-#include "base/state_block/state_block.h"
-#include "base/processor/processor_tracker_landmark_dummy.h"
-#include "base/capture/capture_void.h"
-
-void print_problem_pointers(wolf::ProblemPtr wolf_problem_ptr_)
-{
- using namespace wolf;
- std::cout << "\n-----------\nWolf tree begin" << std::endl;
- std::cout << "Hrd: " << wolf_problem_ptr_->getHardware()->getProblem() << std::endl;
- for (SensorBasePtr sen : wolf_problem_ptr_->getHardware()->getSensorList())
- {
- std::cout << "\tSen: " << sen->getProblem() << std::endl;
- for (ProcessorBasePtr prc : sen->getProcessorList())
- {
- std::cout << "\t\tPrc: " << prc->getProblem() << std::endl;
- }
- }
- std::cout << "Trj: " << wolf_problem_ptr_->getTrajectory()->getProblem() << std::endl;
- for (FrameBasePtr frm : wolf_problem_ptr_->getTrajectory()->getFrameList())
- {
- std::cout << "\tFrm: " << frm->getProblem() << std::endl;
- for (CaptureBasePtr cap : frm->getCaptureList())
- {
- std::cout << "\t\tCap: " << cap->getProblem() << std::endl;
- for (FeatureBasePtr ftr : cap->getFeatureList())
- {
- std::cout << "\t\t\tFtr: " << ftr->getProblem() << std::endl;
- for (FactorBasePtr ctr : ftr->getFactorList())
- {
- std::cout << "\t\t\t\tCtr: " << ctr->getProblem() << std::endl;
- }
- }
- }
- }
- std::cout << "Map: " << wolf_problem_ptr_->getMap()->getProblem() << std::endl;
- for (LandmarkBasePtr lmk : wolf_problem_ptr_->getMap()->getLandmarkList())
- {
- std::cout << "\tLmk: " << lmk->getProblem() << std::endl;
- }
- std::cout << "Wolf tree end\n-----------\n" << std::endl;
-}
-
-int main()
-{
- using namespace wolf;
-
- std::cout << std::endl << "==================== processor tracker landmark test ======================" << std::endl;
-
- // Wolf problem
- ProblemPtr wolf_problem_ptr_ = Problem::create("PO", 2);
- // SensorBasePtr sensor_ptr_ = std::make_shared< SensorBase>("ODOM 2D", std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)),
- // std::make_shared<StateBlock>(Eigen::VectorXs::Zero(1)),
- // std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), 2);
- auto sensor_ptr_ = SensorBase::emplace<SensorBase>(wolf_problem_ptr_->getHardware(), "ODOM 2D", std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)),
- std::make_shared<StateBlock>(Eigen::VectorXs::Zero(1)),
- std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), 2);
- ProcessorParamsTrackerLandmarkPtr params_trk = std::make_shared<ProcessorParamsTrackerLandmark>();
- params_trk->max_new_features = 5;
- params_trk->min_features_for_keyframe = 7;
- params_trk->time_tolerance = 0.25;
- // std::shared_ptr<ProcessorTrackerLandmarkDummy> processor_ptr_ = std::make_shared< ProcessorTrackerLandmarkDummy>(params_trk);
- std::shared_ptr<ProcessorTrackerLandmarkDummy> processor_ptr_ =
- std::static_pointer_cast<ProcessorTrackerLandmarkDummy>(ProcessorBase::emplace<ProcessorTrackerLandmarkDummy>(sensor_ptr_, params_trk));
- // wolf_problem_ptr_->addSensor(sensor_ptr_);
- // sensor_ptr_->addProcessor(processor_ptr_);
-
- std::cout << "sensor & processor created and added to wolf problem" << std::endl;
-
- TimeStamp t(0);
- Scalar dt = 0.5;
- for (auto i = 0; i < 10; i++)
- {
- processor_ptr_->process(std::make_shared<CaptureVoid>(t, sensor_ptr_));
- t += dt;
- }
-
- wolf_problem_ptr_->print(2);
-
- return 0;
-}
-
diff --git a/demos/demo_processor_tracker_landmark_image.cpp b/demos/demo_processor_tracker_landmark_image.cpp
deleted file mode 100644
index 8ac67cf39..000000000
--- a/demos/demo_processor_tracker_landmark_image.cpp
+++ /dev/null
@@ -1,254 +0,0 @@
-//std
-#include <iostream>
-
-#include "base/processor/processor_tracker_landmark_image.h"
-
-//Wolf
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/state_block/state_block.h"
-#include "base/processor/processor_odom_3D.h"
-#include "base/sensor/sensor_odom_3D.h"
-#include "base/sensor/sensor_camera.h"
-#include "base/capture/capture_image.h"
-#include "base/capture/capture_pose.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-
-// Vision utils includes
-#include <vision_utils.h>
-#include <sensors.h>
-#include <common_class/buffer.h>
-#include <common_class/frame.h>
-
-using Eigen::Vector3s;
-using Eigen::Vector4s;
-using Eigen::Vector6s;
-using Eigen::Vector7s;
-
-using namespace wolf;
-
-void cleanupMap(const ProblemPtr& _problem, const TimeStamp& _t, Scalar _dt_max,
- SizeEigen _min_factors)
-{
- std::list<LandmarkBasePtr> lmks_to_remove;
- for (auto lmk : _problem->getMap()->getLandmarkList())
- {
- TimeStamp t0 = std::static_pointer_cast<LandmarkAHP>(lmk)->getAnchorFrame()->getTimeStamp();
- if (_t - t0 > _dt_max)
- if (lmk->getConstrainedByList().size() <= _min_factors)
- lmks_to_remove.push_back(lmk);
- }
-
- for (auto lmk : lmks_to_remove)
- {
- WOLF_DEBUG("Clean up L" , lmk->id() );
- lmk->remove();
- }
-}
-
-Eigen::MatrixXs computeDataCovariance(const VectorXs& _data)
-{
- Scalar k = 0.5;
- Scalar dist = _data.head<3>().norm();
- if ( dist == 0 ) dist = 1.0;
- WOLF_DEBUG("dist: ", dist, "; sigma: ", sqrt(k* (dist + 0.1)) );
- return k * (dist + 0.1) * Matrix6s::Identity();
-}
-
-int main(int argc, char** argv)
-{
- std::cout << std::endl << "==================== processor image landmark test ======================" << std::endl;
-
- // Sensor or sensor recording
- vision_utils::SensorCameraPtr sen_ptr = vision_utils::askUserSource(argc, argv);
- if (sen_ptr==NULL)
- return 0;
-
- unsigned int buffer_size = 10;
- vision_utils::Buffer<vision_utils::FramePtr> frame_buff(buffer_size);
- frame_buff.add( vision_utils::setFrame(sen_ptr->getImage(), 0) );
-
- unsigned int img_width = frame_buff.back()->getImage().cols;
- unsigned int img_height = frame_buff.back()->getImage().rows;
- std::cout << "Image size: " << img_width << "x" << img_height << std::endl;
-
- //=====================================================
- // Environment variable for configuration files
- std::string wolf_root = _WOLF_ROOT_DIR;
- std::cout << wolf_root << std::endl;
- //=====================================================
-
- //=====================================================
- // Wolf problem
- ProblemPtr problem = Problem::create("PO", 3);
-
- // ODOM SENSOR AND PROCESSOR
- SensorBasePtr sensor_base = problem->installSensor("ODOM 3D", "odom", (Vector7s()<<0,0,0,0,0,0,1).finished(), wolf_root + "/src/examples/sensor_odom_3D.yaml");
- SensorOdom3DPtr sensor_odom = std::static_pointer_cast<SensorOdom3D>(sensor_base);
- ProcessorBasePtr prcocessor_base = problem->installProcessor("ODOM 3D", "odometry integrator", "odom", wolf_root + "/src/examples/processor_odom_3D.yaml");
-
- // CAMERA SENSOR AND PROCESSOR
- sensor_base = problem->installSensor("CAMERA", "PinHole", (Vector7s()<<0,0,0,0,0,0,1).finished(), wolf_root + "/src/examples/camera_params_ueye_sim.yaml");
- SensorCameraPtr camera = std::static_pointer_cast<SensorCamera>(sensor_base);
- camera->setImgWidth(img_width);
- camera->setImgHeight(img_height);
- ProcessorTrackerLandmarkImagePtr prc_img_ptr = std::static_pointer_cast<ProcessorTrackerLandmarkImage>( problem->installProcessor("IMAGE LANDMARK", "ORB", "PinHole", wolf_root + "/src/examples/processor_image_feature.yaml") );
- //=====================================================
-
- //=====================================================
- // Origin Key Frame is fixed
- TimeStamp t = 0;
- FrameBasePtr origin_frame = problem->emplaceFrame(KEY, (Vector7s()<<1,0,0,0,0,0,1).finished(), t);
- problem->getProcessorMotion()->setOrigin(origin_frame);
- origin_frame->fix();
-
- std::cout << "t: " << 0 << " \t\t\t x = ( " << problem->getCurrentState().transpose() << ")" << std::endl;
- std::cout << "--------------------------------------------------------------" << std::endl;
- //=====================================================
-
- //=====================================================
- // running CAPTURES preallocated
- CaptureImagePtr image;
- Vector6s data(Vector6s::Zero()); // will integrate this data repeatedly
- CaptureMotionPtr cap_odo = std::make_shared<CaptureMotion>("IMAGE", t, sensor_odom, data, 7, 6, nullptr);
- //=====================================================
-
- //=====================================================
- // Ceres wrapper
- ceres::Solver::Options ceres_options;
- // ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- // ceres_options.max_line_search_step_contraction = 1e-3;
- // ceres_options.minimizer_progress_to_stdout = false;
- // ceres_options.line_search_direction_type = ceres::LBFGS;
- ceres_options.max_num_iterations = 10;
- google::InitGoogleLogging(argv[0]);
-
- CeresManager ceres_manager(problem, ceres_options);
- //=====================================================
-
- //=====================================================
- // graphics
- cv::namedWindow("Feature tracker"); // Creates a window for display.
- cv::moveWindow("Feature tracker", 0, 0);
- cv::startWindowThread();
- //=====================================================
-
- //=====================================================
- // main loop
- unsigned int number_of_KFs = 0;
- Scalar dt = 0.04;
-
- for(int frame_count = 0; frame_count<10000; ++frame_count)
- {
- t += dt;
-
- // Image ---------------------------------------------
-
- frame_buff.add( vision_utils::setFrame(sen_ptr->getImage(), frame_count) );
-
- // Preferred method with factory objects:
- image = std::make_shared<CaptureImage>(t, camera, frame_buff.back()->getImage());
-
- WOLF_DEBUG(__LINE__);
-
- /* process */
- camera->process(image);
-
- WOLF_DEBUG(__LINE__);
-
- // Odometry --------------------------------------------
-
- cap_odo->setTimeStamp(t);
-
- // previous state
- FrameBasePtr prev_key_fr_ptr = problem->getLastKeyFrame();
-// Eigen::Vector7s x_prev = problem->getCurrentState();
- Eigen::Vector7s x_prev = prev_key_fr_ptr->getState();
-
- // before the previous state
- FrameBasePtr prev_prev_key_fr_ptr = nullptr;
- Vector7s x_prev_prev;
- Vector7s dx;
- for (auto f_it = problem->getTrajectory()->getFrameList().rbegin(); f_it != problem->getTrajectory()->getFrameList().rend(); f_it++)
- if ((*f_it) == prev_key_fr_ptr)
- {
- f_it++;
- if (f_it != problem->getTrajectory()->getFrameList().rend())
- {
- prev_prev_key_fr_ptr = (*f_it);
- }
- break;
- }
-
- // compute delta state, and odometry data
- if (!prev_prev_key_fr_ptr)
- {
- // we have just one state --> odometry data is zero
- data.setZero();
- }
- else
- {
- x_prev_prev = prev_prev_key_fr_ptr->getState();
-
- // define local variables on top of existing vectors to avoid memory allocation
- Eigen::Vector3s p_prev_prev(x_prev_prev.data());
- Eigen::Quaternions q_prev_prev(x_prev_prev.data() + 3);
- Eigen::Vector3s p_prev(x_prev.data());
- Eigen::Quaternions q_prev(x_prev.data() + 3);
- Eigen::Vector3s dp(dx.data());
- Eigen::Quaternions dq(dx.data() + 3);
-
- // delta state PQ
- dp = q_prev_prev.conjugate() * (p_prev - p_prev_prev);
- dq = q_prev_prev.conjugate() * q_prev;
-
- // odometry data
- data.head<3>() = dp;
- data.tail<3>() = q2v(dq);
- }
-
- Matrix6s data_cov = computeDataCovariance(data);
-
- cap_odo->setData(data);
- cap_odo->setDataCovariance(data_cov);
-
- sensor_odom->process(cap_odo);
-
-// problem->print(2,1,0,0);
-
-// std::cout << "prev prev ts: " << t_prev_prev.get() << "; x: " << x_prev_prev.transpose() << std::endl;
-// std::cout << "prev ts: " << t_prev.get() << "; x: " << x_prev.transpose() << std::endl;
-// std::cout << "current ts: " << t.get() << std::endl;
-// std::cout << " dt: " << t_prev - t_prev_prev << "; dx: " << dx.transpose() << std::endl;
-
- // Cleanup map ---------------------------------------
-
- cleanupMap(problem, t, 2, 5); // dt, min_ctr
-
- // Solve -----------------------------------------------
- // solve only when new KFs are added
- if (problem->getTrajectory()->getFrameList().size() > number_of_KFs)
- {
- number_of_KFs = problem->getTrajectory()->getFrameList().size();
- std::string summary = ceres_manager.solve(SolverManager::ReportVerbosity::BRIEF);// 0: nothing, 1: BriefReport, 2: FullReport
- std::cout << summary << std::endl;
- }
-
- // Finish loop -----------------------------------------
- cv::Mat image_graphics = frame_buff.back()->getImage().clone();
- prc_img_ptr->drawTrackerRoi(image_graphics, cv::Scalar(255.0, 0.0, 255.0)); //tracker roi
- prc_img_ptr->drawRoi(image_graphics, prc_img_ptr->detector_roi_, cv::Scalar(0.0,255.0, 255.0)); //active search roi
- prc_img_ptr->drawLandmarks(image_graphics);
- prc_img_ptr->drawFeaturesFromLandmarks(image_graphics);
- cv::imshow("Feature tracker", image_graphics);
- cv::waitKey(1);
-
- std::cout << "=================================================================================================" << std::endl;
- }
-
- // problem->print(2);
- problem.reset();
-
- return 0;
-}
-
diff --git a/demos/demo_projection_points.cpp b/demos/demo_projection_points.cpp
deleted file mode 100644
index b9f01912d..000000000
--- a/demos/demo_projection_points.cpp
+++ /dev/null
@@ -1,468 +0,0 @@
-
-// Vision utils
-#include <vision_utils/vision_utils.h>
-
-//std includes
-#include <iostream>
-
-//wolf includes
-#include "base/math/pinhole_tools.h"
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- std::cout << std::endl << " ========= ProjectPoints test ===========" << std::endl << std::endl;
-
- Eigen::MatrixXs points3D(2,3);
- Eigen::Vector3s point3D;
- point3D[0] = 2.0;
- point3D[1] = 5.0;
- point3D[2] = 6.0;
- points3D.row(0)= point3D;
- point3D[0] = 4.0;
- point3D[1] = 2.0;
- point3D[2] = 1.0;
- points3D.row(1)= point3D;
-
- Eigen::Vector3s cam_ext_rot_mat = Eigen::Vector3s::Zero();
- Eigen::Vector3s cam_ext_trans_mat = Eigen::Vector3s::Ones();
-
- Eigen::Matrix3s cam_intr_mat;
- cam_intr_mat = Eigen::Matrix3s::Identity();
- cam_intr_mat(0,2)=2;
- cam_intr_mat(1,2)=2;
-
- Eigen::VectorXs dist_coef(5);
- dist_coef << 0,0,0,0,0;
-
- Eigen::MatrixXs points2D = vision_utils::projectPoints(points3D, cam_ext_rot_mat, cam_ext_trans_mat, cam_intr_mat, dist_coef);
-
- for (int ii = 0; ii < points3D.rows(); ++ii)
- std::cout << "points2D- X: " << points2D(ii,0) << "; Y: " << points2D(ii,1) << std::endl;
-
- std::cout << std::endl << " ========= PinholeTools DUALITY TEST ===========" << std::endl << std::endl;
-
- //================================= projectPoint and backprojectPoint to/from NormalizedPlane
-
- Eigen::Vector3s project_point_normalized_test;
- project_point_normalized_test[0] = 1.06065;
- project_point_normalized_test[1] = 1.06065;
- project_point_normalized_test[2] = 3;
- Eigen::Vector2s project_point_normalized_output;
- Eigen::Vector2s project_point_normalized_output2;
- Scalar project_point_normalized_dist;
-
- Scalar backproject_point_normalized_depth = 3;
- Eigen::Vector3s backproject_point_normalized_output;
-
- project_point_normalized_output = pinhole::projectPointToNormalizedPlane(project_point_normalized_test);
-
- pinhole::projectPointToNormalizedPlane(project_point_normalized_test,
- project_point_normalized_output2,
- project_point_normalized_dist);
-
- backproject_point_normalized_output =
- pinhole::backprojectPointFromNormalizedPlane(project_point_normalized_output,
- backproject_point_normalized_depth);
-
- std::cout << "TEST project and backproject PointToNormalizedPlane" << std::endl;
- std::cout << std:: endl << "Original " << project_point_normalized_test.transpose() << std::endl;
- std::cout << std:: endl << "Project " << project_point_normalized_output.transpose() << std::endl;
- std::cout << std:: endl << "Alternate project" << project_point_normalized_output.transpose() << std::endl;
- std::cout << std:: endl << "Backproject " << backproject_point_normalized_output.transpose() << std::endl;
-
- //================================= projectPoint and backprojectPoint to/from NormalizedPlane WITH JACOBIANS
-
- Eigen::Vector3s pp_normalized_test;
- pp_normalized_test[0] = 3;
- pp_normalized_test[1] = 3;
- pp_normalized_test[2] = 3;
- Eigen::Vector2s pp_normalized_output;
- Eigen::Vector2s pp_normalized_output2;
- Eigen::Matrix<Scalar, 2, 3> pp_normalized_jacobian;
- Eigen::Matrix<Scalar, 2, 3> pp_normalized_jacobian2;
- Scalar pp_normalized_distance;
-
- Scalar bpp_normalized_depth = 3;
- Eigen::Vector3s bpp_normalized_output;
- Eigen::Matrix<Scalar, 3, 2> bpp_normalized_jacobian;
- Eigen::Vector3s bpp_normalized_jacobian_depth;
-
- pinhole::projectPointToNormalizedPlane(pp_normalized_test,
- pp_normalized_output,
- pp_normalized_jacobian);
- pinhole::projectPointToNormalizedPlane(pp_normalized_test,
- pp_normalized_output2,
- pp_normalized_distance,
- pp_normalized_jacobian2);
-
- pinhole::backprojectPointFromNormalizedPlane(pp_normalized_output,
- bpp_normalized_depth,
- bpp_normalized_output,
- bpp_normalized_jacobian,
- bpp_normalized_jacobian_depth);
-
- std::cout << "\n--------------------------------------------------------" << std::endl;
- std::cout << "\nTEST project and backproject PointToNormalizedPlane with JACOBIAN" << std::endl;
-
- std::cout << std:: endl << "Original" << pp_normalized_test.transpose() << std::endl;
- std::cout << std:: endl << "Project" << pp_normalized_output.transpose() << std::endl;
- std::cout << "\n--> Jacobian" << std::endl << pp_normalized_jacobian << std::endl;
-
- std::cout << std:: endl << "Alternate project" << pp_normalized_output2.transpose() << "; distance: "
- << pp_normalized_distance << std::endl;
- std::cout << "\n--> Jacobian" << std::endl << pp_normalized_jacobian2 << std::endl;
-
- std::cout << std:: endl << "Backproject" << bpp_normalized_output.transpose()
- << "; depth: " << bpp_normalized_depth << std::endl;
- std::cout << "\n--> Jacobian" << std::endl << bpp_normalized_jacobian << std::endl;
- std::cout << "\n--> Jacobian - depth" << bpp_normalized_jacobian_depth.transpose() << std::endl;
-
- Eigen::Matrix2s test_jacobian; // (2x3) * (3x2) = (2x2)
- test_jacobian = pp_normalized_jacobian * bpp_normalized_jacobian;
-
- std::cout << "\n\n\n==> Jacobian Testing" << std::endl << test_jacobian << std::endl;
-
- //================================= IsInRoi / IsInImage
-
- Eigen::Vector2s pix;
- pix[0] = 40; // x
- pix[1] = 40; // y
-
- int roi_x = 30;
- int roi_y = 30;
- int roi_width = 20;
- int roi_height = 20;
-
- int image_width = 640;
- int image_height = 480;
-
- bool is_in_roi;
- bool is_in_image;
- is_in_roi = pinhole::isInRoi(pix,
- roi_x,
- roi_y,
- roi_width,
- roi_height);
- is_in_image = pinhole::isInImage(pix,
- image_width,
- image_height);
-
- std::cout << "\n--------------------------------------------------------" << std::endl;
- std::cout << "\nTEST isInRoi/isInImage" << std::endl;
- std::cout << std::endl << "Pixel " << std::endl;
- std::cout << "x: " << pix[0] << "; y: " << pix[1] << std::endl;
- std::cout << std::endl << "ROI " << std::endl;
- std::cout << "x: " << roi_x << "; y: " << roi_y << "; width: " << roi_width << "; height: " << roi_height << std::endl;
- std::cout << "is_in_roi: " << is_in_roi << std::endl;
- std::cout << std::endl << "Image " << std::endl;
- std::cout << "width: " << image_width << "; height: " << image_height << std::endl;
- std::cout << "is_in_image: " << is_in_image << std::endl;
-
- //================================= computeCorrectionModel
-
- Eigen::Vector2s distortion2;
- distortion2[0] = -0.301701;
- distortion2[1] = 0.0963189;
- Eigen::Vector4s k_test2;
- //k = [u0, v0, au, av]
- k_test2[0] = 516.686; //u0
- k_test2[1] = 355.129; //v0
- k_test2[2] = 991.852; //au
- k_test2[3] = 995.269; //av
-
- Eigen::Vector2s correction_test2;
- pinhole::computeCorrectionModel(k_test2,
- distortion2,
- correction_test2);
-
- std::cout << "\n--------------------------------------------------------" << std::endl;
- std::cout << "\nTEST computeCorrectionModel" << std::endl;
- std::cout << std::endl << "distortion" << std::endl;
- std::cout << "d1: " << distortion2[0] << "; d2: " << distortion2[1] << std::endl;
- std::cout << std::endl << "k values" << std::endl;
- std::cout << "u0: " << k_test2[0] << "; v0: " << k_test2[1] << "; au: " << k_test2[2] << "; av: " << k_test2[3] << std::endl;
- std::cout << std::endl << "correction" << std::endl;
- std::cout << "c1: " << correction_test2[0] << "; c2: " << correction_test2[1] << std::endl;
-
- //================================= distortPoint
-
- Eigen::Vector2s distorting_point;
- distorting_point[0] = 0.35355;
- distorting_point[1] = 0.35355;
-
- Eigen::Vector2s distored_point3;
- distored_point3 = pinhole::distortPoint(distortion2,
- distorting_point);
-
- std::cout << "\n--------------------------------------------------------" << std::endl;
- std::cout << "\nTEST distortPoint" << std::endl;
- std::cout << std::endl << "Point to be distorted" << std::endl;
- std::cout << "x: " << distorting_point[0] << "; y: " << distorting_point[1] << std::endl;
- std::cout << std::endl << "Distorted point" << std::endl;
- std::cout << "x: " << distored_point3[0] << "; y: " << distored_point3[1] << std::endl;
-
- Eigen::Vector2s corrected_point4;
- corrected_point4 = pinhole::undistortPoint(correction_test2,
- distored_point3);
- std::cout << std::endl << "Corrected point" << std::endl;
- std::cout << "x: " << corrected_point4[0] << "; y: " << corrected_point4[1] << std::endl;
-
- ////
-
- Eigen::Vector2s distored_point4;
- Eigen::Matrix2s distortion_jacobian2;
- pinhole::distortPoint(distortion2,
- distorting_point,
- distored_point4,
- distortion_jacobian2);
-
- std::cout << "\n\nTEST distortPoint, jacobian" << std::endl;
- std::cout << std::endl << "Point to be distorted" << std::endl;
- std::cout << "x: " << distorting_point[0] << "; y: " << distorting_point[1] << std::endl;
- std::cout << std::endl << "Distorted point" << std::endl;
- std::cout << "x: " << distored_point4[0] << "; y: " << distored_point4[1] << std::endl;
- std::cout << "\n--> Jacobian" << std::endl <<
- distortion_jacobian2 << std::endl;
-
- Eigen::Vector2s corrected_point5;
- Eigen::Matrix2s corrected_jacobian2;
- pinhole::undistortPoint(correction_test2,
- distored_point4,
- corrected_point5,
- corrected_jacobian2);
-
- std::cout << std::endl << "Corrected point" << std::endl;
- std::cout << "x: " << corrected_point5[0] << "; y: " << corrected_point5[1] << std::endl;
- std::cout << "\n--> Jacobian" << std::endl <<
- corrected_jacobian2 << std::endl;
-
- Eigen::Matrix2s test_jacobian_distortion;
- test_jacobian_distortion = distortion_jacobian2 * corrected_jacobian2;
-
- std::cout << "\n\n\n==> Jacobian Testing" << std::endl <<
- test_jacobian_distortion << std::endl;
-
- //================================= PixelizePoint
-
- Eigen::Vector2s pixelize_ud;
- pixelize_ud[0] = 45;
- pixelize_ud[1] = 28;
-
- Eigen::Vector2s pixelize_output3;
- pixelize_output3 = pinhole::pixellizePoint(k_test2,
- pixelize_ud);
-
- std::cout << "\n--------------------------------------------------------" << std::endl;
- std::cout << "\nTEST pixelizePoint; Eigen::Vector2s" << std::endl;
- std::cout << std::endl << "Original" << std::endl;
- std::cout << "x: " << pixelize_ud[0] << "; y: " << pixelize_ud[1] << std::endl;
- std::cout << std::endl << "Pixelized" << std::endl;
- std::cout << "x: " << pixelize_output3[0] << "; y: " << pixelize_output3[1] << std::endl;
-
- Eigen::Vector2s depixelize_output3;
- depixelize_output3 = pinhole::depixellizePoint(k_test2,
- pixelize_output3);
- std::cout << std::endl << "Depixelized" << std::endl;
- std::cout << "x: " << depixelize_output3[0] << "; y: " << depixelize_output3[1] << std::endl;
-
- ////
-
- Eigen::Vector2s pixelize_output4;
- Eigen::Matrix2s pixelize_jacobian2;
- pinhole::pixellizePoint(k_test2,
- pixelize_ud,
- pixelize_output4,
- pixelize_jacobian2);
-
- std::cout << std::endl << "TEST pixelizePoint; Jacobians" << std::endl;
- std::cout << std::endl << "Original" << std::endl;
- std::cout << "x: " << pixelize_ud[0] << "; y: " << pixelize_ud[1] << std::endl;
- std::cout << std::endl << "Pixelized" << std::endl;
- std::cout << "x: " << pixelize_output4[0] << "; y: " << pixelize_output4[1] << std::endl;
- std::cout << "\n--> Jacobian" << std::endl <<
- pixelize_jacobian2 << std::endl;
-
- Eigen::Vector2s depixelize_output4;
- Eigen::Matrix2s depixelize_jacobian2;
- pinhole::depixellizePoint(k_test2,
- pixelize_output4,
- depixelize_output4,
- depixelize_jacobian2);
-
- std::cout << std::endl << "Depixelized" << std::endl;
- std::cout << "x: " << depixelize_output4[0] << "; y: " << depixelize_output4[1] << std::endl;
- std::cout << "\n--> Jacobian" << std::endl <<
- depixelize_jacobian2 << std::endl;
-
- Eigen::Matrix2s test_jacobian_pix;
- test_jacobian_pix = pixelize_jacobian2 * depixelize_jacobian2;
-
- std::cout << "\n\n\n==> Jacobian Testing" << std::endl <<
- test_jacobian_pix << std::endl;
-
- //================================= projectPoint Complete
-
-// //distortion
-// distortion2;
-
-// //k
-// k_test2;
-
-// //3Dpoint
-// project_point_normalized_test;
-
- Eigen::Vector2s point2D_test5;
- point2D_test5 = pinhole::projectPoint(k_test2,
- distortion2,
- project_point_normalized_test);
-
- std::cout << "\n--------------------------------------------------------" << std::endl;
- std::cout << std::endl << "TEST projectPoint Complete" << std::endl;
- std::cout << "\nPARAMS" << std::endl;
- std::cout << "\nDistortion:" << std::endl;
- std::cout << "d1: " << distortion2[0] << "; d2: " << distortion2[1] << std::endl << std::endl;
- std::cout << "k values:" << std::endl;
- std::cout << "u0: " << k_test2[0] << "; v0: " << k_test2[1] << "; au: " << k_test2[2] << "; av: " << k_test2[3] << std::endl << std::endl;
- std::cout << "3D Point" << std::endl;
- std::cout << "x: " << project_point_normalized_test[0] << "; y: " << project_point_normalized_test[1]
- << "; z: " << project_point_normalized_test[2] << std::endl;
- std::cout << "\n\n\nFirst function output" << std::endl;
- std::cout << "x: " << point2D_test5[0] << "; y: " << point2D_test5[1] << std::endl;
-
- //distance
- Eigen::Vector2s point2D_test6;
- Scalar distance_test4;
- pinhole::projectPoint(k_test2,
- distortion2,
- project_point_normalized_test,
- point2D_test6,
- distance_test4);
-
- std::cout << std::endl << "Second function output" << std::endl;
- std::cout << "x: " << point2D_test6[0] << "; y: " << point2D_test6[1] << "; dist: " << distance_test4 << std::endl;
-
- //jacobian
- Eigen::Vector2s point2D_test7;
- Eigen::MatrixXs jacobian_test3(2,3);
- pinhole::projectPoint(k_test2,
- distortion2,
- project_point_normalized_test,
- point2D_test7,
- jacobian_test3);
-
- std::cout << std::endl << "Third function output" << std::endl;
- std::cout << "x: " << point2D_test7[0] << "; y: " << point2D_test7[1] << std::endl;
- std::cout << "\n-->Jacobian" << std::endl <<
- jacobian_test3 << std::endl;
-
- //jacobian and distance
- Eigen::Vector2s point2D_test8;
- Eigen::MatrixXs jacobian_test4(2,3);
- Scalar distance_test3;
- pinhole::projectPoint(k_test2,
- distortion2,
- project_point_normalized_test,
- point2D_test8,
- distance_test3,
- jacobian_test4);
-
- std::cout << std::endl << "Fourth function output" << std::endl;
- std::cout << "x: " << point2D_test8[0] << "; y: " << point2D_test8[1] << "; dist: " << distance_test3 << std::endl;
- std::cout << "\n-->Jacobian" << std::endl <<
- jacobian_test4 << std::endl;
-
- /////////////////////////////
-
-// //correction
-// correction_test2
-
-// //2Dpoint
-// point2D_test5
-
- Scalar depth3 = project_point_normalized_test[2];
-
- Eigen::Vector3s point3D_backproj5;
- point3D_backproj5 = pinhole::backprojectPoint(k_test2,
- correction_test2,
- point2D_test5,
- depth3);
-
- std::cout << "\n\nTEST backprojectPoint Complete" << std::endl;
- std::cout << std::endl << "First function output" << std::endl;
- std::cout << "x: " << point3D_backproj5[0] << "; y: " << point3D_backproj5[1] << "; z: " << point3D_backproj5[2] << std::endl;
-
- //jacobian
- Eigen::Vector3s point3D_backproj4;
- Eigen::MatrixXs jacobian_backproj2(3,2);
- Eigen::Vector3s depth_jacobian2;
- pinhole::backprojectPoint(k_test2,
- correction_test2,
- point2D_test7,
- depth3,
- point3D_backproj4,
- jacobian_backproj2,
- depth_jacobian2);
-
- std::cout << std::endl << "Second function output" << std::endl;
- std::cout << "x: " << point3D_backproj4[0] << "; y: " << point3D_backproj4[1] << "; z: " << point3D_backproj4[2] << std::endl;
- std::cout << "\n--> Jacobian" << std::endl <<
- jacobian_backproj2 << std::endl;
- std::cout << "\n--> Jacobian - depth" << std::endl <<
- depth_jacobian2[0] << " " << depth_jacobian2[1] << " " << depth_jacobian2[2] << " " << std::endl;
-
- Eigen::Matrix2s test_jacobian_complete;
- test_jacobian_complete = jacobian_test4 * jacobian_backproj2;
-
- std::cout << "\n\n\n==> Jacobian Testing" << std::endl <<
- test_jacobian_complete << std::endl;
-
- /* Test */
- std::cout << "\n\n\n\nTEST\n" << std::endl;
-
- Eigen::Matrix3s K;
- K(0,0) = 830.748734; K(0,1) = 0; K(0,2) = 327.219132;
- K(1,0) = 0; K(1,1) = 831.18208; K(1,2) = 234.720244;
- K(2,0) = 0; K(2,1) = 0; K(2,2) = 1;
-
- Eigen::Vector4s K_params = {327.219132,234.720244, 830.748734,831.18208};
-
- std::cout << "K:\n" << K << std::endl;
-
- Eigen::Vector4s distortion_vector = {0.0006579999999999999, 0.023847, -0.001878, 0.007706999999999999};
-
- std::cout << "\nDistortion vector:\n" << distortion_vector << std::endl;
-
- Eigen::Vector4s correction_vector;
- pinhole::computeCorrectionModel(K_params,
- distortion_vector,
- correction_vector);
-
- std::cout << "\nCorrection vector:\n" << correction_vector << std::endl;
-
- Eigen::Vector3s test_point3D;
- Eigen::Vector2s test_point2D = {123,321};
- std::cout << "\ntest_point2D ORIGINAL:\n" << test_point2D << std::endl;
-
- test_point2D = pinhole::depixellizePoint(K_params,
- test_point2D);
- std::cout << "\ntest_point2D DEPIXELIZED:\n" << test_point2D << std::endl;
- test_point2D = pinhole::undistortPoint(correction_vector,
- test_point2D);
- std::cout << "\ntest_point2D UNDISTORTED:\n" << test_point2D << std::endl;
- test_point3D = pinhole::backprojectPointFromNormalizedPlane(test_point2D,
- 2);
- std::cout << "\ntest_point3D BACKPROJECTED:\n" << test_point3D << std::endl;
-
- test_point2D = pinhole::projectPointToNormalizedPlane(test_point3D);
- std::cout << "\ntest_point2D NORMALIZED:\n" << test_point2D << std::endl;
- test_point2D = pinhole::distortPoint(distortion_vector,
- test_point2D);
- std::cout << "\ntest_point2D DISTORTED:\n" << test_point2D << std::endl;
- test_point2D = pinhole::pixellizePoint(K_params,
- test_point2D);
- std::cout << "\ntest_point2D PIXELIZED:\n" << test_point2D << std::endl;
-
-}
-
diff --git a/demos/demo_sh_ptr.cpp b/demos/demo_sh_ptr.cpp
deleted file mode 100644
index 3a10903c8..000000000
--- a/demos/demo_sh_ptr.cpp
+++ /dev/null
@@ -1,795 +0,0 @@
-/**
- * \file test_sh_ptr.cpp
- *
- * Created on: Oct 4, 2016
- * \author: jsola
- *
- * Complete Wolf tree skeleton with smart pointers
- *
- */
-
-// C++11
-#include <memory>
-
-using std::shared_ptr;
-using std::weak_ptr;
-using std::make_shared;
-using std::enable_shared_from_this;
-
-// std
-#include <list>
-#include <vector>
-#include <iostream>
-using std::list;
-using std::vector;
-using std::cout;
-using std::endl;
-
-namespace wolf
-{
-// fwds
-class H; // hardware
-class S; // sensor
-class p; // processor
-class T; // trajectory
-class F; // frame
-class C; // capture
-class f; // feature
-class c; // factor
-class M; // map
-class L; // landmark
-
-//////////////////////////////////////////////////////////////////////////////////
-// DECLARE WOLF TREE
-
-class P : public enable_shared_from_this<P>
-{
- private:
- shared_ptr<H> H_ptr_;
- shared_ptr<T> T_ptr_;
- shared_ptr<M> M_ptr_;
-
- public:
- P();
- ~P(){cout << "destruct P" << endl;}
- void setup();
- shared_ptr<H> getH(){return H_ptr_;}
- shared_ptr<T> getT(){return T_ptr_;}
- shared_ptr<M> getM(){return M_ptr_;}
-};
-
-class H : public enable_shared_from_this<H>
-{
- private:
- weak_ptr<P> P_ptr_;
- list<shared_ptr<S>> S_list_;
-
- public:
- H(){cout << "construct H" << endl;}
- ~H(){cout << "destruct H" << endl;}
- shared_ptr<P> getP(){
- shared_ptr<P> P_sh = P_ptr_.lock();
- return P_sh;
- }
- void setP(const shared_ptr<P> _P){P_ptr_ = _P;}
- list<shared_ptr<S>>& getSlist() {return S_list_;}
- shared_ptr<S> add_S(shared_ptr<S> _S);
-};
-
-class S : public enable_shared_from_this<S>
-{
- private:
- weak_ptr<P> P_ptr_;
- weak_ptr<H> H_ptr_;
- list<shared_ptr<p>> p_list_;
- static int id_count_;
-
- // list<shared_ptr<C>> C_list_; // List of all captures
-
- public:
- int id;
- S():id(++id_count_){cout << "construct + S" << id << endl;}
- ~S(){cout << "destruct + S" << id << endl;}
- shared_ptr<P> getP(){
- shared_ptr<P> P_sh = P_ptr_.lock();
- if (!P_sh)
- P_sh = getH()->getP();
- return P_sh;
- }
- void setP(const shared_ptr<P>& _P){P_ptr_ = _P;}
- shared_ptr<H> getH(){
- shared_ptr<H> H_sh = H_ptr_.lock();
- return H_sh;
- }
- void setH(const shared_ptr<H> _H){H_ptr_ = _H;}
- list<shared_ptr<p>>& getplist() {return p_list_;}
- shared_ptr<p> add_p(shared_ptr<p> _p);
-};
-
-class p : public enable_shared_from_this<p>
-{
- private:
- weak_ptr<P> P_ptr_;
- weak_ptr<S> S_ptr_;
- static int id_count_;
-
- public:
- int id;
- p():id(++id_count_){cout << "construct + p" << id << endl;}
- ~p(){cout << "destruct + p" << id << endl;}
- shared_ptr<P> getP(){
- shared_ptr<P> P_sh = P_ptr_.lock();
- if (!P_sh)
- P_sh = getS()->getP();
- return P_sh;
- }
- void setP(const shared_ptr<P>& _P){P_ptr_ = _P;}
- shared_ptr<S> getS(){
- shared_ptr<S> S_sh = S_ptr_.lock();
- return S_sh;
- }
- void setS(const shared_ptr<S> _S){S_ptr_ = _S;}
-};
-
-class T : public enable_shared_from_this<T>
-{
- private:
- weak_ptr<P> P_ptr_;
- list<shared_ptr<F>> F_list_;
-
- public:
- T(){cout << "construct T" << endl;}
- ~T(){cout << "destruct T" << endl;}
- shared_ptr<P> getP(){
- shared_ptr<P> P_sh = P_ptr_.lock();
- return P_sh;
- }
- void setP(const shared_ptr<P> _P){P_ptr_ = _P;}
- list<shared_ptr<F>>& getFlist() {return F_list_;}
- shared_ptr<F> add_F(shared_ptr<F> _F);
-};
-
-class F : public enable_shared_from_this<F>
-{
- private:
- weak_ptr<P> P_ptr_;
- weak_ptr<T> T_ptr_;
- list<shared_ptr<C>> C_list_;
-
- list<shared_ptr<c>> c_by_list; // list of factors to this frame
-
- static int id_count_;
- bool is_removing;
-
- public:
- int id;
- F() :is_removing(false),id(++id_count_){cout << "construct + F" << id << endl;}
- ~F(){cout << "destruct + F" << id << endl;}
- shared_ptr<P> getP(){
- shared_ptr<P> P_sh = P_ptr_.lock();
- if (!P_sh)
- P_sh = getT()->getP();
- return P_sh;
- }
- void setP(const shared_ptr<P>& _P){P_ptr_ = _P;}
- shared_ptr<T> getT(){
- shared_ptr<T> T_sh = T_ptr_.lock();
- return T_sh;
- }
- void setT(const shared_ptr<T> _T){T_ptr_ = _T;}
- list<shared_ptr<C>>& getClist() {return C_list_;}
- list<shared_ptr<c>>& getCbyList(){return c_by_list;}
- shared_ptr<C> add_C(shared_ptr<C> _C);
- void add_c_by(shared_ptr<c> _cby)
- {
- c_by_list.push_back(_cby);
- }
- void remove();
-
-};
-
-class C : public enable_shared_from_this<C>
-{
- private:
- weak_ptr<P> P_ptr_;
- weak_ptr<F> F_ptr_;
- list<shared_ptr<f>> f_list_;
-
- weak_ptr<S> S_ptr_; // sensor
- static int id_count_;
- bool is_deleting;
-
- public:
- int id;
- C():is_deleting(false),id(++id_count_){cout << "construct + C" << id << endl;}
- ~C(){cout << "destruct + C" << id << endl;}
- shared_ptr<P> getP(){
- shared_ptr<P> P_sh = P_ptr_.lock();
- if (!P_sh)
- P_sh = getF()->getP();
- return P_sh;
- }
- void setP(const shared_ptr<P>& _P){P_ptr_ = _P;}
- shared_ptr<F> getF(){
- shared_ptr<F> F_sh = F_ptr_.lock();
- return F_sh;
- }
- void setF(const shared_ptr<F> _F){F_ptr_ = _F;}
- list<shared_ptr<f>>& getflist() {return f_list_;}
- shared_ptr<f> add_f(shared_ptr<f> _f);
- void remove();
-
-};
-
-class f : public enable_shared_from_this<f>
-{
- private:
- weak_ptr<P> P_ptr_;
- weak_ptr<C> C_ptr_;
- list<shared_ptr<c>> c_list_;
-
- list<shared_ptr<c>> c_by_list; // list of factors to this feature
-
- static int id_count_;
- bool is_deleting;
-
- public:
- int id;
- f():is_deleting(false),id(++id_count_){cout << "construct + f" << id << endl;}
- ~f(){cout << "destruct + f" << id << endl;}
- shared_ptr<P> getP(){
- shared_ptr<P> P_sh = P_ptr_.lock();
- if (!P_sh)
- P_sh = getC()->getP();
- return P_sh;
- }
- void setP(const shared_ptr<P>& _P){P_ptr_ = _P;}
- shared_ptr<C> getC(){
- shared_ptr<C> C_sh = C_ptr_.lock();
- return C_sh;
- }
- void setC(const shared_ptr<C> _C){C_ptr_ = _C;}
- list<shared_ptr<c>>& getclist() {return c_list_;}
- list<shared_ptr<c>>& getCbyList(){return c_by_list;}
- shared_ptr<c> add_c(shared_ptr<c> _c);
- void add_c_by(shared_ptr<c> _cby)
- {
- c_by_list.push_back(_cby);
- }
- void remove();
-};
-
-class c : public enable_shared_from_this<c>
-{
- private:
- weak_ptr<P> P_ptr_;
- weak_ptr<f> f_ptr_; // change this to shared??
-
- // can we have just one pointer? Derive 3 classes from c?
- weak_ptr<F> F_other_ptr_; // change this to shared?
- weak_ptr<f> f_other_ptr_; // change this to shared?
- weak_ptr<L> L_other_ptr_; // change this to shared?
-
- static int id_count_;
- bool is_deleting;
-
- public:
- int id;
- enum{c0, cF, cf, cL} type;
- c():is_deleting(false),id(++id_count_){type = c0; cout << "construct + c" << id << endl;}
- c(shared_ptr<F> _F_other);
- c(shared_ptr<f> _f_other);
- c(shared_ptr<L> _L_other);
- ~c(){cout << "destruct + c" << id << endl;}
- shared_ptr<P> getP(){
- shared_ptr<P> P_sh = P_ptr_.lock();
- if (!P_sh)
- P_sh = getf()->getP();
- return P_sh;
- }
- void setP(const shared_ptr<P>& _P){P_ptr_ = _P;}
- shared_ptr<f> getf(){
- shared_ptr<f> f_sh = f_ptr_.lock();
- return f_sh;
- }
- void setf(const shared_ptr<f> _f){f_ptr_ = _f;}
- shared_ptr<F> getFother(){return F_other_ptr_.lock();}
- shared_ptr<f> getfother(){return f_other_ptr_.lock();}
- shared_ptr<L> getLother(){return L_other_ptr_.lock();}
- void remove();
-};
-
-class M : public enable_shared_from_this<M>
-{
- private:
- weak_ptr<P> P_ptr_;
- list<shared_ptr<L>> L_list_;
-
- public:
- M(){cout << "construct M" << endl;}
- ~M(){cout << "destruct M" << endl;}
- shared_ptr<P> getP(){
- shared_ptr<P> P_sh = P_ptr_.lock();
- return P_sh;
- }
- void setP(const shared_ptr<P> _P){P_ptr_ = _P;}
- list<shared_ptr<L>>& getLlist() {return L_list_;}
- shared_ptr<L> add_L(shared_ptr<L> _L);
-};
-
-class L : public enable_shared_from_this<L>
-{
- private:
- weak_ptr<P> P_ptr_;
- weak_ptr<M> M_ptr_;
-
- list<shared_ptr<c>> c_by_list; // list of factors to this landmark
-
- static int id_count_;
- bool is_deleting;
-
- public:
- int id;
- L():is_deleting(false),id(++id_count_){cout << "construct + L" << id << endl;}
- ~L(){cout << "destruct + L" << id << endl;}
- shared_ptr<P> getP(){
- shared_ptr<P> P_sh = P_ptr_.lock();
- if (!P_sh)
- P_sh = getM()->getP();
- return P_sh;
- }
- void setP(const shared_ptr<P>& _P){P_ptr_ = _P;}
- shared_ptr<M> getM(){
- shared_ptr<M> M_sh = M_ptr_.lock();
- return M_sh;
- }
- void setM(const shared_ptr<M> _M){M_ptr_ = _M;}
- list<shared_ptr<c>>& getCbyList(){return c_by_list;}
- void add_c_by(shared_ptr<c> _cby)
- {
- c_by_list.push_back(_cby);
- }
- void remove();
-};
-
-//////////////////////////////////////////////////////////////////////////////////
-// IMPLEMENTATION of some methods
-
-P::P(){
- cout << "construct P" << endl;
- H_ptr_ = make_shared<H>();
- T_ptr_ = make_shared<T>();
- M_ptr_ = make_shared<M>();
- cout << "P is constructed" << endl;
-}
-
-void P::setup()
-{
- H_ptr_->setP(shared_from_this());
- T_ptr_->setP(shared_from_this());
- M_ptr_->setP(shared_from_this());
- cout << "P is set up" << endl;
-}
-
-shared_ptr<S> H::add_S(shared_ptr<S> _S)
-{
- S_list_.push_back(_S);
- _S->setH(shared_from_this());
- _S->setP(getP());
- return _S;
-}
-
-shared_ptr<p> S::add_p(shared_ptr<p> _p)
-{
- p_list_.push_back(_p);
- _p->setS(shared_from_this());
- _p->setP(getP());
- return _p;
-}
-
-shared_ptr<F> T::add_F(shared_ptr<F> _F)
-{
- F_list_.push_back(_F);
- _F->setT(shared_from_this());
- _F->setP(getP());
- return _F;
-}
-
-shared_ptr<C> F::add_C(shared_ptr<C> _C)
-{
- C_list_.push_back(_C);
- _C->setF(shared_from_this());
- _C->setP(getP());
- return _C;
-}
-void F::remove()
-{
- if (!is_removing)
- {
- is_removing = true;
- cout << "Removing F" << id << endl;
- shared_ptr<F> this_F = shared_from_this(); // keep this alive while removing it
- getT()->getFlist().remove(this_F); // remove from upstream
- while (!C_list_.empty())
- C_list_.front()->remove(); // remove downstream
- while (!c_by_list.empty())
- c_by_list.front()->remove(); // remove constrained
- }
-}
-
-shared_ptr<f> C::add_f(shared_ptr<f> _f)
-{
- f_list_.push_back(_f);
- _f->setC(shared_from_this());
- _f->setP(getP());
- return _f;
-}
-void C::remove()
-{
- if (!is_deleting)
- {
- is_deleting = true;
- cout << "Removing C" << id << endl;
- shared_ptr<C> this_C = shared_from_this(); // keep this alive while removing it
- getF()->getClist().remove(this_C); // remove from upstream
- if (getF()->getClist().empty() && getF()->getCbyList().empty())
- getF()->remove(); // remove upstream
- while (!f_list_.empty())
- f_list_.front()->remove(); // remove downstream
- }
-}
-
-shared_ptr<c> f::add_c(shared_ptr<c> _c)
-{
- c_list_.push_back(_c);
- _c->setf(shared_from_this());
- _c->setP(getP());
- return _c;
-}
-void f::remove()
-{
- if (!is_deleting)
- {
- is_deleting = true;
- cout << "Removing f" << id << endl;
- shared_ptr<f> this_f = shared_from_this(); // keep this alive while removing it
- getC()->getflist().remove(this_f); // remove from upstream
- if (getC()->getflist().empty())
- getC()->remove(); // remove upstream
- while (!c_list_.empty())
- c_list_.front()->remove(); // remove downstream
- while (!c_by_list.empty())
- c_by_list.front()->remove(); // remove constrained
- }
-}
-
-c::c(shared_ptr<F> _F_other):is_deleting(false),id(++id_count_)
-{
- cout << "construct + c" << id << " -> F" << _F_other->id << endl;
- type = cF;
- F_other_ptr_ = _F_other;
-}
-
-c::c(shared_ptr<f> _f_other):is_deleting(false),id(++id_count_)
-{
- cout << "construct + c" << id << " -> f" << _f_other->id << endl;
- type = cf;
- f_other_ptr_ = _f_other;
-}
-
-c::c(shared_ptr<L> _L_other):is_deleting(false),id(++id_count_)
-{
- cout << "construct + c" << id << " -> L" << _L_other->id << endl;
- type = cL;
- L_other_ptr_ = _L_other;
-}
-
-void c::remove()
-{
- if (!is_deleting)
- {
- is_deleting = true;
- cout << "Removing c" << id << endl;
- shared_ptr<c> this_c = shared_from_this(); // keep this alive while removing it
- getf()->getclist().remove(this_c); // remove from upstream
- if (getf()->getclist().empty() && getf()->getCbyList().empty())
- getf()->remove(); // remove upstream
-
- // remove other: {Frame, feature, Landmark}
- switch (type)
- {
- case c::cF:
- getFother()->getCbyList().remove(this_c);
- if (getFother()->getCbyList().empty() && getFother()->getClist().empty())
- getFother()->remove();
- break;
- case c::cf:
- getfother()->getCbyList().remove(this_c);
- if (getfother()->getCbyList().empty() && getfother()->getclist().empty())
- getfother()->remove();
- break;
- case c::cL:
- getLother()->getCbyList().remove(this_c);
- if (getLother()->getCbyList().empty())
- getLother()->remove();
- break;
- default:
- break;
- }
- }
-}
-
-shared_ptr<L> M::add_L(shared_ptr<L> _L)
-{
- L_list_.push_back(_L);
- _L->setM(shared_from_this());
- _L->setP(getP());
- return _L;
-}
-
-void L::remove()
-{
- if (!is_deleting)
- {
- is_deleting = true;
- cout << "Removing L" << id << endl;
- shared_ptr<L> this_L = shared_from_this(); // keep this alive while removing it
- getM()->getLlist().remove(this_L); // remove from upstream
- while (!c_by_list.empty())
- c_by_list.front()->remove(); // remove constrained
- }
-}
-
-}
-
-//////////////////////////////////////////////////////////////////////////////////
-// HELPERS
-
-using namespace wolf;
-
-void print_cF(const shared_ptr<P>& Pp)
-{
- cout << "Frame factors" << endl;
- for (auto Fp : Pp->getT()->getFlist())
- {
- cout << "F" << Fp->id << " @ " << Fp.get() << endl;
- for (auto cp : Fp->getCbyList())
- {
- cout << " -> c" << cp->id << " @ " << cp.get()
- << " -> F" << cp->getFother()->id << " @ " << cp->getFother().get() << endl;
- }
- }
-}
-
-void print_cf(const shared_ptr<P>& Pp)
-{
- cout << "Feature factors" << endl;
- for (auto Fp : Pp->getT()->getFlist())
- {
- for (auto Cp : Fp->getClist())
- {
- for (auto fp : Cp->getflist())
- {
- cout << "f" << fp->id << " @ " << fp.get() << endl;
- for (auto cp : fp->getCbyList())
- {
- cout << " -> c" << cp->id << " @ " << cp.get()
- << " -> f" << cp->getfother()->id << " @ " << cp->getfother().get() << endl;
- }
- }
- }
- }
-}
-
-void print_cL(const shared_ptr<P>& Pp)
-{
- cout << "Landmark factors" << endl;
- for (auto Lp : Pp->getM()->getLlist())
- {
- cout << "L" << Lp->id << " @ " << Lp.get() << endl;
- for (auto cp : Lp->getCbyList())
- {
- cout << " -> c" << cp->id << " @ " << cp.get()
- << " -> L" << cp->getLother()->id << " @ " << cp->getLother().get() << endl;
- }
- }
-}
-
-void print_c(const shared_ptr<P>& Pp)
-{
- cout << "All factors" << endl;
- for (auto Fp : Pp->getT()->getFlist())
- {
- for (auto Cp : Fp->getClist())
- {
- for (auto fp : Cp->getflist())
- {
- for (auto cp : fp->getclist())
- {
- if (cp)
- {
- switch (cp->type)
- {
- case c::cF:
- cout << "c" << cp->id << " @ " << cp.get()
- << " -> F" << cp->getFother()->id << " @ " << cp->getFother() << endl;
- break;
- case c::cf:
- cout << "c" << cp->id << " @ " << cp.get()
- << " -> f" << cp->getfother()->id << " @ " << cp->getfother() << endl;
- break;
- case c::cL:
- cout << "c" << cp->id << " @ " << cp.get()
- << " -> L" << cp->getLother()->id << " @ " << cp->getLother() << endl;
- break;
- default:
- cout << "Bad factor" << endl;
- break;
- }
- }
- }
- }
- }
- }
-}
-
-/** Build problem
- * See the problem built here:
- * https://docs.google.com/drawings/d/1vYmhBjJz7AHxOdy0gV-77hqsOYfGVuvUmnRVB-Zfp_Q/edit
- */
-shared_ptr<P> buildProblem(int N)
-{
- shared_ptr<P> Pp = make_shared<P>();
- Pp->setup();
- // H
- for (int Si = 0; Si < 2; Si++)
- {
- shared_ptr<S> Sp = Pp->getH()->add_S(make_shared<S>());
- for (int pi = 0; pi < 2; pi++)
- {
- shared_ptr<p> pp = Sp->add_p(make_shared<p>());
- }
- }
- // M
- for (int Li = 0; Li < 2; Li++)
- {
- shared_ptr<L> Lp = Pp->getM()->add_L(make_shared<L>());
- }
- // T
- list<shared_ptr<L> >::iterator Lit = Pp->getM()->getLlist().begin();
- vector<weak_ptr<F> > Fvec(N);
- for (int Fi = 0; Fi < N; Fi++)
- {
- shared_ptr<F> Fp = Pp->getT()->add_F(make_shared<F>());
- Fvec.at(Fi) = Fp;
- for (int Ci = 0; Ci < 2; Ci++)
- {
- shared_ptr<C> Cp = Fp->add_C(make_shared<C>());
- for (int fi = 0; fi < 1; fi++)
- {
- shared_ptr<f> fp = Cp->add_f(make_shared<f>());
- if (Ci || !Fi) // landmark factor
- {
- shared_ptr<c> cp = fp->add_c(make_shared<c>(*Lit));
- (*Lit)->add_c_by(cp);
- Lit++;
- if (Lit == Pp->getM()->getLlist().end())
- Lit = Pp->getM()->getLlist().begin();
- }
- else // motion factor
- {
- shared_ptr<F> Fp = Fvec.at(Fi-1).lock();
- if (Fp)
- {
- shared_ptr<c> cp = fp->add_c(make_shared<c>(Fp));
- Fp->add_c_by(cp);
- }
- else
- cout << "Could not constrain Frame" << endl;
- }
- }
- }
- }
- return Pp;
-}
-
-// init ID factories
-int S::id_count_ = 0;
-int p::id_count_ = 0;
-int F::id_count_ = 0;
-int C::id_count_ = 0;
-int f::id_count_ = 0;
-int c::id_count_ = 0;
-int L::id_count_ = 0;
-
-// tests
-void removeFactors(const shared_ptr<P>& Pp)
-{
- cout << "Removing factor type L ----------" << endl;
- Pp->getT()->getFlist().front()->getClist().front()->getflist().front()->getclist().front()->remove();
- cout << "Removing factor type L ----------" << endl;
- Pp->getT()->getFlist().front()->getClist().front()->getflist().front()->getclist().front()->remove();
- cout << "Removing factor type F ----------" << endl;
- Pp->getT()->getFlist().back()->getClist().front()->getflist().front()->getclist().front()->remove();
- cout << "Removing factor type L ----------" << endl;
- Pp->getT()->getFlist().back()->getClist().back()->getflist().front()->getclist().front()->remove();
- cout << "Removing factor type F ----------" << endl;
- Pp->getT()->getFlist().back()->getClist().front()->getflist().front()->getclist().front()->remove();
-}
-
-void removeLandmarks(const shared_ptr<P>& Pp)
-{
- cout << "Removing landmark ----------" << endl;
- Pp->getM()->getLlist().front()->remove();
- cout << "Removing landmark ----------" << endl;
- Pp->getM()->getLlist().front()->remove();
-}
-
-void removeFrames(const shared_ptr<P>& Pp)
-{
- cout << "Removing frame ----------" << endl;
- Pp->getT()->getFlist().back()->remove();
- cout << "Removing frame ----------" << endl;
- Pp->getT()->getFlist().front()->remove();
- cout << "Removing frame ----------" << endl;
- Pp->getT()->getFlist().back()->remove();
-}
-
-void removeLmksAndFrames(const shared_ptr<P>& Pp)
-{
- cout << "Removing landmark ----------" << endl;
- Pp->getM()->getLlist().front()->remove();
- cout << "Removing frame ----------" << endl;
- Pp->getT()->getFlist().front()->remove();
- cout << "Removing frame ----------" << endl;
- Pp->getT()->getFlist().back()->remove();
-}
-
-//////////////////////////////////////////////////////////////////////////////////
-// MAIN
-int main()
-{
- int N = 3;
-
- shared_ptr<P> Pp = buildProblem(N);
- cout << "Wolf tree created ----------------------------" << endl;
-
- cout << "\nShowing factors --------------------------" << endl;
- cout<<endl;
- print_cF(Pp);
- cout<<endl;
- print_cf(Pp);
- cout<<endl;
- print_cL(Pp);
- cout<<endl;
- print_c(Pp);
-
- //------------------------------------------------------------------
- // Several tests. Uncomment the desired test.
- // Run only one test at a time, otherwise you'll get segfaults!
-
-// cout << "\nRemoving factors -------------------------" << endl;
-// removeFactors(Pp);
-
-// cout << "\nRemoving landmarks ---------------------------" << endl;
-// removeLandmarks(Pp);
-
-// cout << "\nRemoving frames ------------------------------" << endl;
-// removeFrames(Pp);
-
- cout << "\nRemoving lmks and frames ------------------------------" << endl;
- removeLmksAndFrames(Pp);
-
-// cout << "\nRemoving problem ---------------------------" << endl;
-// Pp.reset();
-
-// cout << "\nRebuilding problem ---------------------------" << endl;
-// Pp = buildProblem(N);
-
- //------------------------------------------------------------------
-
- cout << "\nExiting main() -------------------------------" << endl;
-
- return 1;
-}
-
diff --git a/demos/demo_simple_AHP.cpp b/demos/demo_simple_AHP.cpp
deleted file mode 100644
index 23ea39de7..000000000
--- a/demos/demo_simple_AHP.cpp
+++ /dev/null
@@ -1,257 +0,0 @@
-/**
- * \file test_simple_AHP.cpp
- *
- * Created on: 2 nov. 2016
- * \author: jtarraso
- */
-
-#include "base/common/wolf.h"
-#include "base/frame/frame_base.h"
-#include "base/math/pinhole_tools.h"
-#include "base/sensor/sensor_camera.h"
-#include "base/math/rotations.h"
-#include "base/capture/capture_image.h"
-#include "base/landmark/landmark_AHP.h"
-#include "base/factor/factor_AHP.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-
-// Vision utils
-#include <vision_utils/vision_utils.h>
-
-/**
- * This test simulates the following situation:
- * - A kf at the origin, we use it as anchor: kf1
- * - A kf at the origin, we use it to project lmks onto the anchor frame: kf2
- * - A kf at 1m to the right of the origin, kf3
- * - A kf at 1m to the left of the origin, kf4
- * - A lmk at 1m distance in front of the anchor: L1
- * - we use this lmk to project it onto kf2, kf3 and kf4 and obtain measured pixels p0, p1 and p2
- * - A lmk initialized at kf1, with measurement p0, at a distance of 2m: L2
- * - we project the pixels p3 and p4: we observe that they do not match p1 and p2
- * - we use the measurements p1 and p2 to solve the optimization problem on L2: L2 should converge to L1.
- * - This is a sketch of the situation:
- * - X, Y are the axes in world frame
- * - x, z are the axes in anchor camera frame. We have that X=z, Y=-x.
- * - Axes Z and y are perpendicular to the drawing; they have no effect.
- *
- * X,z
- * ^
- * |
- * L2 * 2
- * .|.
- * . | .
- * . | .
- * . | .
- * . L1 * 1 .
- * . . | . .
- * . . | . .
- * p4 . . | . . p3
- * .. p2 | p1 ..
- * Y <--+---------+---------+
- * -x +1 0 -1
- * kf4 kf1 kf3
- * kf2
- *
- * camera: (uo,vo) = (320,240)
- * (au,av) = (320,320)
- *
- * projection geometry:
- *
- * 1:1 2:1 1:0 2:1 1:1
- * 0 160 320 480 640
- * +----+----+----+----+
- * |
- * | 320
- * |
- * *
- *
- * projected pixels:
- * p0 = (320,240) // at optical axis or relation 1:0
- * p1 = ( 0 ,240) // at 45 deg or relation 1:1
- * p2 = (640,240) // at 45 deg or relation 1:1
- * p3 = (160,240) // at a relation 2:1
- * p4 = (480,240) // at a relation 2:1
- *
- */
-int main(int argc, char** argv)
-{
- using namespace wolf;
- using namespace Eigen;
-
- /* 1. crear 2 kf, fixed
- * 2. crear 1 sensor
- * 3. crear 1 lmk1
- * 4. projectar lmk sobre sensor a fk1
- * 5. projectar lmk sobre sensor a kf4
- * 6. // esborrar lmk lmk_ptr->remove() no cal
- * 7. crear nous kf
- * 8. crear captures
- * 9. crear features amb les mesures de 4 i 5
- * 10. crear lmk2 des de kf3
- * 11. crear factor des del kf4 a lmk2, amb ancora al kf3
- * 12. solve
- * 13. lmk1 == lmk2 ?
- */
-
- // ============================================================================================================
- /* 1 */
- ProblemPtr problem = Problem::create("PO", 3);
- // One anchor frame to define the lmk, and a copy to make a factor
- FrameBasePtr kf_1 = problem->emplaceFrame(KEY,(Vector7s()<<0,0,0,0,0,0,1).finished(), TimeStamp(0));
- FrameBasePtr kf_2 = problem->emplaceFrame(KEY,(Vector7s()<<0,0,0,0,0,0,1).finished(), TimeStamp(0));
- // and two other frames to observe the lmk
- FrameBasePtr kf_3 = problem->emplaceFrame(KEY,(Vector7s()<<0,-1,0,0,0,0,1).finished(), TimeStamp(0));
- FrameBasePtr kf_4 = problem->emplaceFrame(KEY,(Vector7s()<<0,+1,0,0,0,0,1).finished(), TimeStamp(0));
-
- kf_1->fix();
- kf_2->fix();
- kf_3->fix();
- kf_4->fix();
- // ============================================================================================================
-
- // ============================================================================================================
- /* 2 */
- std::string wolf_root = _WOLF_ROOT_DIR;
- SensorBasePtr sensor_ptr = problem->installSensor("CAMERA", "PinHole", (Vector7s()<<0,0,0,-0.5,0.5,-0.5,0.5).finished(), wolf_root + "/src/examples/camera_params_ueye_sim.yaml");
- SensorCameraPtr camera = std::static_pointer_cast<SensorCamera>(sensor_ptr);
- // ============================================================================================================
-
- // ============================================================================================================
- /* 3 */
- Eigen::Vector3s lmk_dir = {0,0,1}; // in the optical axis of the anchor camera at kf1
- std::cout << std::endl << "lmk: " << lmk_dir.transpose() << std::endl;
- lmk_dir.normalize();
- Eigen::Vector4s lmk_hmg_c;
- Scalar distance = 1.0; // from anchor at kf1
- lmk_hmg_c = {lmk_dir(0),lmk_dir(1),lmk_dir(2),(1/distance)};
-// std::cout << "lmk hmg in C frame: " << lmk_hmg_c.transpose() << std::endl;
- // ============================================================================================================
-
- // Captures------------------
- cv::Mat cv_image;
- cv_image.zeros(2,2,0);
- CaptureImagePtr image_0 = std::make_shared<CaptureImage>(TimeStamp(0), camera, cv_image);
- CaptureImagePtr image_1 = std::make_shared<CaptureImage>(TimeStamp(1), camera, cv_image);
- CaptureImagePtr image_2 = std::make_shared<CaptureImage>(TimeStamp(2), camera, cv_image);
- kf_2->addCapture(image_0);
- kf_3->addCapture(image_1);
- kf_4->addCapture(image_2);
-
- // Features-----------------
- cv::Mat desc;
-
- cv::KeyPoint kp_0;
- FeaturePointImagePtr feat_0 = std::make_shared<FeaturePointImage>(kp_0, 0, desc, Eigen::Matrix2s::Identity());
- image_0->addFeature(feat_0);
-
- cv::KeyPoint kp_1;
- FeaturePointImagePtr feat_1 = std::make_shared<FeaturePointImage>(kp_1, 0, desc, Eigen::Matrix2s::Identity());
- image_1->addFeature(feat_1);
-
- cv::KeyPoint kp_2;
- FeaturePointImagePtr feat_2 = std::make_shared<FeaturePointImage>(kp_2, 0, desc, Eigen::Matrix2s::Identity());
- image_2->addFeature(feat_2);
-
- // Landmark--------------------
- LandmarkAHPPtr lmk_1 = std::make_shared<LandmarkAHP>(lmk_hmg_c, kf_1, camera, desc);
- problem->addLandmark(lmk_1);
- lmk_1->fix();
- std::cout << "Landmark 1: " << lmk_1->point().transpose() << std::endl;
-
- // Factors------------------
- FactorAHPPtr fac_0 = FactorAHP::create(feat_0, lmk_1, nullptr);
- feat_0->addFactor(fac_0);
- FactorAHPPtr fac_1 = FactorAHP::create(feat_1, lmk_1, nullptr);
- feat_1->addFactor(fac_1);
- FactorAHPPtr fac_2 = FactorAHP::create(feat_2, lmk_1, nullptr);
- feat_2->addFactor(fac_2);
-
- // Projections----------------------------
- Eigen::VectorXs pix_0 = fac_0->expectation();
- kp_0 = cv::KeyPoint(pix_0(0), pix_0(1), 0);
- feat_0->setKeypoint(kp_0);
-
- Eigen::VectorXs pix_1 = fac_1->expectation();
- kp_1 = cv::KeyPoint(pix_1(0), pix_1(1), 0);
- feat_1->setKeypoint(kp_1);
-
- Eigen::VectorXs pix_2 = fac_2->expectation();
- kp_2 = cv::KeyPoint(pix_2(0), pix_2(1), 0);
- feat_2->setKeypoint(kp_2);
-
- std::cout << "pixel 0: " << pix_0.transpose() << std::endl;
- std::cout << "pixel 1: " << pix_1.transpose() << std::endl;
- std::cout << "pixel 2: " << pix_2.transpose() << std::endl;
- //
- //======== up to here the initial projections ==============
-
- std::cout << "\n";
-
- //======== now we want to estimate a new lmk ===============
- //
- // Features -----------------
- FeaturePointImagePtr feat_3 = std::make_shared<FeaturePointImage>(kp_1, 0, desc, Eigen::Matrix2s::Identity());
- image_1->addFeature(feat_3);
-
- FeaturePointImagePtr feat_4 = std::make_shared<FeaturePointImage>(kp_2, 0, desc, Eigen::Matrix2s::Identity());
- image_2->addFeature(feat_4);
-
- // New landmark with measured pixels from kf2 (anchor) kf3 and kf4 (measurements)
- Scalar unknown_distance = 2; // the real distance is 1
- Matrix3s K = camera->getIntrinsicMatrix();
- Vector3s pix_0_hmg;
- pix_0_hmg << pix_0, 1;
- Eigen::Vector3s dir_0 = K.inverse() * pix_0_hmg;
- Eigen::Vector4s pnt_hmg_0;
- pnt_hmg_0 << dir_0, 1/unknown_distance;
- LandmarkAHPPtr lmk_2( std::make_shared<LandmarkAHP>(pnt_hmg_0, kf_2, camera, desc) );
- problem->addLandmark(lmk_2);
- std::cout << "Landmark 2: " << lmk_2->point().transpose() << std::endl;
-
- // New factors from kf3 and kf4
- FactorAHPPtr fac_3 = FactorAHP::create(feat_3, lmk_2, nullptr);
- feat_3->addFactor(fac_3);
- FactorAHPPtr fac_4 = FactorAHP::create(feat_4, lmk_2, nullptr);
- feat_4->addFactor(fac_4);
-
- Eigen::Vector2s pix_3 = fac_3->expectation();
- Eigen::Vector2s pix_4 = fac_4->expectation();
-
- std::cout << "pix 3: " << pix_3.transpose() << std::endl;
- std::cout << "pix 4: " << pix_4.transpose() << std::endl;
-
- // Wolf tree status ----------------------
- problem->print(3);
-// problem->check();
-
- // ========== solve ==================================================================================================
- /* 12 */
- // Ceres wrapper
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- // ceres_options.minimizer_progress_to_stdout = false;
- // ceres_options.line_search_direction_type = ceres::LBFGS;
- // ceres_options.max_num_iterations = 100;
- google::InitGoogleLogging(argv[0]);
-
- CeresManager ceres_manager(problem, ceres_options);
-
- std::string summary = ceres_manager.solve(SolverManager::ReportVerbosity::FULL);// 0: nothing, 1: BriefReport, 2: FullReport
- std::cout << summary << std::endl;
-
- // Test of convergence over the lmk params
- bool pass = (lmk_2->point() - lmk_1->point()).isMuchSmallerThan(1,Constants::EPS);
-
- std::cout << "Landmark 2 below should have converged to Landmark 1:" << std::endl;
- std::cout << "Landmark 1: " << lmk_1->point().transpose() << std::endl;
- std::cout << "Landmark 2: " << lmk_2->point().transpose() << std::endl;
- std::cout << "Landmark convergence test " << (pass ? "PASSED" : "FAILED") << std::endl;
- std::cout << std::endl;
-
- if (!pass)
- return -1;
- return 0;
-
-}
-
diff --git a/demos/demo_sort_keyframes.cpp b/demos/demo_sort_keyframes.cpp
deleted file mode 100644
index 036ed1250..000000000
--- a/demos/demo_sort_keyframes.cpp
+++ /dev/null
@@ -1,79 +0,0 @@
-/**
- * \file test_sort_keyframes.cpp
- *
- * Created on: May 24, 2016
- * \author: jvallve
- */
-
-// Wolf includes
-#include "base/common/wolf.h"
-#include "base/problem/problem.h"
-#include "base/frame/frame_base.h"
-#include "base/trajectory/trajectory_base.h"
-
-// STL includes
-#include <list>
-#include <memory>
-
-// General includes
-#include <iostream>
-
-using namespace wolf;
-
-void printFrames(ProblemPtr _problem_ptr)
-{
- std::cout << "TRAJECTORY:" << std::endl;
- for (auto frm : _problem_ptr->getTrajectory()->getFrameList())
- std::cout << "\t " << (frm->isKey() ? "KEY FRAME: " : "FRAME: ") << frm->id() << " - TS: " << frm->getTimeStamp().getSeconds() << "." << frm->getTimeStamp().getNanoSeconds() << std::endl;
-}
-
-int main()
-{
- ProblemPtr problem_ptr = Problem::create(FRM_PO_2D);
-
- problem_ptr->emplaceFrame(NON_ESTIMATED, Eigen::VectorXs::Zero(3), TimeStamp(0.1));
- FrameBasePtr frm2 = problem_ptr->emplaceFrame(NON_ESTIMATED, Eigen::VectorXs::Zero(3), TimeStamp(0.2));
- FrameBasePtr frm3 = problem_ptr->emplaceFrame(NON_ESTIMATED, Eigen::VectorXs::Zero(3), TimeStamp(0.3));
- problem_ptr->emplaceFrame(NON_ESTIMATED, Eigen::VectorXs::Zero(3), TimeStamp(0.4));
- FrameBasePtr frm5 = problem_ptr->emplaceFrame(NON_ESTIMATED, Eigen::VectorXs::Zero(3), TimeStamp(0.5));
- FrameBasePtr frm6 = problem_ptr->emplaceFrame(NON_ESTIMATED, Eigen::VectorXs::Zero(3), TimeStamp(0.6));
-
- printFrames(problem_ptr);
-
- std::cout << std::endl << "Frame " << frm5->id() << " set KEY" << std::endl;
- frm5->setEstimated();
-
- printFrames(problem_ptr);
-
- std::cout << std::endl << "Frame " << frm2->id() << " set KEY" << std::endl;
- frm2->setEstimated();
-
- printFrames(problem_ptr);
-
- std::cout << std::endl << "Frame " << frm3->id() << " new TimeStamp:" << 0.45 << std::endl;
- frm3->setTimeStamp(TimeStamp(0.45));
-
- printFrames(problem_ptr);
-
- std::cout << std::endl << "Frame " << frm3->id() << " set KEY" << std::endl;
- frm3->setEstimated();
-
- printFrames(problem_ptr);
-
- std::cout << std::endl << "Frame " << frm6->id() << " set KEY" << std::endl;
- frm6->setEstimated();
-
- printFrames(problem_ptr);
-
- FrameBasePtr frm7 = problem_ptr->emplaceFrame(KEY, Eigen::VectorXs::Zero(3), TimeStamp(0.7));
- std::cout << std::endl << "created Key Frame " << frm7->id() << " TS: " << 0.7 << std::endl;
-
- printFrames(problem_ptr);
-
- FrameBasePtr frm8 = problem_ptr->emplaceFrame(KEY, Eigen::VectorXs::Zero(3), TimeStamp(0.35));
- std::cout << std::endl << "created Key Frame " << frm8->id() << " TS: " << 0.35 << std::endl;
-
- printFrames(problem_ptr);
-
- return 0;
-}
diff --git a/demos/demo_sparsification.cpp b/demos/demo_sparsification.cpp
deleted file mode 100644
index a521cabd1..000000000
--- a/demos/demo_sparsification.cpp
+++ /dev/null
@@ -1,314 +0,0 @@
-// Sparsification example creating wolf tree from imported graph from .txt file
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-//std includes
-#include <cstdlib>
-#include <fstream>
-#include <string>
-#include <iostream>
-#include <memory>
-#include <random>
-#include <cmath>
-#include <queue>
-
-//Wolf includes
-#include "core/capture/capture_void.h"
-#include "core/feature/feature_odom_2D.h"
-#include "core/factor/factor_base.h"
-#include "core/ceres_wrapper/ceres_manager.h"
-
-// EIGEN
-//#include <Eigen/CholmodSupport>
-#include <Eigen/StdVector> // Eigen in std vector
-
-namespace wolf{
-// inserts the sparse matrix 'ins' into the sparse matrix 'original' in the place given by 'row' and 'col' integers
-
-void insertSparseBlock(const Eigen::SparseMatrix<Scalar>& ins, Eigen::SparseMatrix<Scalar>& original, const unsigned int& row, const unsigned int& col)
-{
- for (int k=0; k<ins.outerSize(); ++k)
- for (Eigen::SparseMatrix<Scalar>::InnerIterator iti(ins,k); iti; ++iti)
- original.coeffRef(iti.row() + row, iti.col() + col) = iti.value();
-
- original.makeCompressed();
-}
-
-void decodeEdge(const std::string& buffer, unsigned int& edge_from, unsigned int& edge_to, Eigen::Vector3s& measurement, Eigen::Matrix3s& covariance)
-{
- std::string str_num;
-
- unsigned int i = 0;
-
- // only decode edges
- if (buffer.at(0) == 'E')
- {
- //skip rest of EDGE word
- while (buffer.at(i) != ' ') i++;
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // FROM ID
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- edge_from = atoi(str_num.c_str())+1;
- str_num.clear();
-
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // TO ID
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- edge_to = atoi(str_num.c_str())+1;
- str_num.clear();
-
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // MEASUREMENT
- // X
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- measurement(0) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // Y
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- measurement(1) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // THETA
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- measurement(2) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // INFORMATION
- Eigen::Matrix3s information;
- // XX
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(0,0) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // XY
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(0,1) = atof(str_num.c_str());
- information(1,0) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // YY
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(1,1) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // THETATHETA
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(2,2) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // XTHETA
- while (buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(0,2) = atof(str_num.c_str());
- information(2,0) = atof(str_num.c_str());
- str_num.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // YTHETA
- while (i < buffer.size() && buffer.at(i) != ' ')
- str_num.push_back(buffer.at(i++));
- information(1,2) = atof(str_num.c_str());
- information(2,1) = atof(str_num.c_str());
- str_num.clear();
-
- // COVARIANCE
- covariance = information.inverse();
- }
- else
- {
- edge_from = 0;
- edge_to = 0;
- }
-}
-
-}
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- //Welcome message
- std::cout << std::endl << " ========= WOLF IMPORTED .graph TEST ===========" << std::endl << std::endl;
-
- bool wrong_input = false;
- if (argc < 3)
- wrong_input = true;
- else if (argc > 4)
- wrong_input = true;
- else if (argc > 2 && (atoi(argv[2]) < 2 || atoi(argv[2]) > 5))
- wrong_input = true;
- else if (argc > 3 && atoi(argv[3]) < 0 )
- wrong_input = true;
-
- if (wrong_input)
- {
- std::cout << "Please call me with: [./test_wolf_imported_graph DATASET T (MAX_VERTICES)], where:" << std::endl;
- std::cout << " DATASET: manhattan, killian or intel" << std::endl;
- std::cout << " T keep one node each T: 2, 3, 4 or 5" << std::endl;
- std::cout << " optional: MAX_VERTICES max edges to be loaded" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
-
- // input variables
- char const * dataset_path = std::getenv("DATASET_PATH");
- unsigned int pruning_T = atoi(argv[2]);
- std::string file_path(dataset_path);
- file_path = file_path + "/graphs/redirected_" + std::to_string(pruning_T) + "_" + argv[1] + ".graph";
- unsigned int MAX_VERTEX = 1e9;
- if (argc > 3 && atoi(argv[3]) != 0)
- MAX_VERTEX = atoi(argv[3]);
-
- // Wolf problem
- FrameBasePtr last_frame_ptr, frame_from_ptr, frame_to_ptr;
- ProblemPtr bl_problem_ptr = Problem::create("PO_2D");
- SensorBasePtr sensor_ptr = bl_problem_ptr->installSensor("ODOM 2D", "Odometry", Eigen::VectorXs::Zero(3), IntrinsicsBasePtr());
-
- // Ceres wrapper
- std::string bl_summary, sp_summary;
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- ceres_options.max_num_iterations = 10;
- CeresManagerPtr bl_ceres_manager = std::make_shared<CeresManager>(bl_problem_ptr, ceres_options);
-
- // load graph from .txt
- std::ifstream graph_file;
- graph_file.open(file_path.c_str(), std::ifstream::in);
- if (!graph_file.is_open())
- {
- printf("\nError opening file: %s\n",file_path.c_str());
- return -1;
- }
-
- // auxiliar variables
- std::string line_string;
- unsigned int edge_from, edge_to;
- Eigen::Vector3s meas;
- Eigen::Matrix3s meas_cov;
- Eigen::Matrix3s R = Eigen::Matrix3s::Identity();
- //clock_t t1;
-
- // ------------------------ START EXPERIMENT ------------------------
- // First frame FIXED
- last_frame_ptr = bl_problem_ptr->emplaceFrame(KEY, Eigen::Vector3s::Zero(),TimeStamp(0));
- last_frame_ptr->fix();
- bl_problem_ptr->print(4, true, false, true);
-
- while (std::getline(graph_file, line_string) && last_frame_ptr->id() <= MAX_VERTEX)
- {
- std::cout << "new line:" << line_string << std::endl;
- decodeEdge(line_string, edge_from, edge_to, meas, meas_cov);
-
- // only factors
- if (edge_from != 0)
- {
-
- // ODOMETRY -------------------
- if (edge_to > last_frame_ptr->id())
- {
- frame_from_ptr = last_frame_ptr;
-
- // NEW KEYFRAME
- Eigen::Vector3s from_pose = frame_from_ptr->getState();
- R.topLeftCorner(2,2) = Eigen::Rotation2Ds(from_pose(2)).matrix();
- Eigen::Vector3s new_frame_pose = from_pose + R*meas;
- last_frame_ptr = bl_problem_ptr->emplaceFrame(KEY, new_frame_pose, TimeStamp(double(edge_to)));
-
- frame_to_ptr = last_frame_ptr;
-
- std::cout << "NEW FRAME " << last_frame_ptr->id() << " - ts = " << last_frame_ptr->getTimeStamp().get() << std::endl;
-
- // REMOVE PREVIOUS NODES
- }
- // LOOP CLOSURE ---------------
- else
- {
- if (edge_from == last_frame_ptr->id())
- frame_from_ptr = last_frame_ptr;
- else
- for (auto frm_rit = bl_problem_ptr->getTrajectory()->getFrameList().rbegin(); frm_rit != bl_problem_ptr->getTrajectory()->getFrameList().rend(); frm_rit++)
- if ((*frm_rit)->id() == edge_from)
- {
- frame_from_ptr = *frm_rit;
- break;
- }
- if (edge_to == last_frame_ptr->id())
- frame_to_ptr = last_frame_ptr;
- else
- for (auto frm_rit = bl_problem_ptr->getTrajectory()->getFrameList().rbegin(); frm_rit != bl_problem_ptr->getTrajectory()->getFrameList().rend(); frm_rit++)
- if ((*frm_rit)->id() == edge_to)
- {
- frame_to_ptr = *frm_rit;
- break;
- }
- }
-// std::cout << "frame_from " << frame_from_ptr->id() << std::endl;
-// std::cout << "edge_from " << edge_from << std::endl;
-// std::cout << "frame_to " << frame_to_ptr->id() << std::endl;
-// std::cout << "edge_to " << edge_to << std::endl;
-
- assert(frame_from_ptr->id() == edge_from && "frame from id and edge from idx must be the same");
- assert(frame_to_ptr->id() == edge_to && "frame to id and edge to idx must be the same");
-
- // CAPTURE
- CaptureVoidPtr capture_ptr = std::make_shared<CaptureVoid>(TimeStamp(0), sensor_ptr);
- frame_from_ptr->addCapture(capture_ptr);
-
- // FEATURE
- FeatureBasePtr feature_ptr = std::make_shared<FeatureOdom2D>(meas, meas_cov);
- capture_ptr->addFeature(feature_ptr);
-
- // CONSTRAINT
- FactorOdom2DPtr factor_ptr = std::make_shared<FactorOdom2D>(feature_ptr, frame_to_ptr);
- feature_ptr->addFactor(factor_ptr);
- frame_to_ptr->addConstrainedBy(factor_ptr);
-
- // SOLVE
- // solution
- bl_summary = bl_ceres_manager->solve(SolverManager::ReportVerbosity::FULL);
- std::cout << bl_summary << std::endl;
-
- // covariance
- bl_ceres_manager->computeCovariances(SolverManager::CovarianceBlocksToBeComputed::ALL);//ALL_MARGINALS
-
- // t1 = clock();
- // double t_sigma_manual = 0;
- // t_sigma_manual += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- }
- }
-
- //bl_problem_ptr->print(4, true, false, true);
-
- //End message
- std::cout << " =========================== END ===============================" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_state_quaternion.cpp b/demos/demo_state_quaternion.cpp
deleted file mode 100644
index 0fabac44e..000000000
--- a/demos/demo_state_quaternion.cpp
+++ /dev/null
@@ -1,39 +0,0 @@
-/*
- * \file test_state_quaternion.cpp
- *
- * Created on: Mar 7, 2016
- * \author: jsola
- */
-
-#include "base/frame/frame_base.h"
-#include "base/state_block/state_quaternion.h"
-#include "base/common/time_stamp.h"
-
-#include <iostream>
-
-int main (void)
-{
- using namespace wolf;
-
- // 3D
- StateBlockPtr pp = std::make_shared<StateBlock>(3);
- StateQuaternionPtr op = std::make_shared<StateQuaternion>();
- StateBlockPtr vp = std::make_shared<StateBlock>(3);
-
- TimeStamp t;
-
- FrameBase pqv(t,pp,op,vp);
-
- std::cout << "P local param: " << pqv.getP()->getLocalParametrization() << std::endl;
- std::cout << "Q local param: " << pqv.getO()->getLocalParametrization() << std::endl;
- std::cout << "V local param: " << pqv.getV()->getLocalParametrization() << std::endl;
-
- // delete pp;
- // delete op;
- // delete vp;
- // Note: Deleting the StateBlock pointers will be done at the destruction of FrameBase.
-
- std::cout << "Done" << std::endl;
-
- return 1;
-}
diff --git a/demos/demo_tracker_ORB.cpp b/demos/demo_tracker_ORB.cpp
deleted file mode 100644
index 89ea1800a..000000000
--- a/demos/demo_tracker_ORB.cpp
+++ /dev/null
@@ -1,267 +0,0 @@
-//std includes
-#include <iostream>
-
-// Vision utils
-#include <vision_utils.h>
-#include <sensors.h>
-#include <common_class/buffer.h>
-#include <common_class/frame.h>
-#include <detectors/orb/detector_orb.h>
-#include <descriptors/orb/descriptor_orb.h>
-#include <matchers/bruteforce_hamming_2/matcher_bruteforce_hamming_2.h>
-
-//Wolf
-#include "core/processor/processor_tracker_landmark_image.h"
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- std::cout << std::endl << "==================== tracker ORB test ======================" << std::endl;
-
- //=====================================================
- // Environment variable for configuration files
- std::string wolf_root = _WOLF_ROOT_DIR;
- //=====================================================
-
- //=====================================================
-
- // Sensor or sensor recording
- vision_utils::SensorCameraPtr sen_ptr = vision_utils::askUserSource(argc, argv);
- if (sen_ptr==NULL)
- return 0;
-
- // Detector
- vision_utils::DetectorParamsORBPtr params_det = std::make_shared<vision_utils::DetectorParamsORB>();
-
- params_det->nfeatures = 500; // The maximum number of features to retain.
- params_det->scaleFactor = 2; // Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor will mean that to cover certain scale range you will need more pyramid levels and so the speed will suffer.
- params_det->nlevels = 8; // The number of pyramid levels. The smallest level will have linear size equal to input_image_linear_size/pow(scaleFactor, nlevels).
- params_det->edgeThreshold = 16; // This is size of the border where the features are not detected. It should roughly match the patchSize parameter.
- params_det->firstLevel = 0; // It should be 0 in the current implementation.
- params_det->WTA_K = 2; // The number of points that produce each element of the oriented BRIEF descriptor. The default value 2 means the BRIEF where we take a random point pair and compare their brightnesses, so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3 random points (of course, those point coordinates are random, but they are generated from the pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such output will occupy 2 bits, and therefore it will need a special variant of Hamming distance, denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).
- params_det->scoreType = cv::ORB::HARRIS_SCORE; //#enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };
- params_det->patchSize = 31;
-
- vision_utils::DetectorBasePtr det_b_ptr = vision_utils::setupDetector("ORB", "ORB detector", params_det);
- vision_utils::DetectorORBPtr det_ptr = std::static_pointer_cast<vision_utils::DetectorORB>(det_b_ptr);
-
- // Descriptor
- vision_utils::DescriptorParamsORBPtr params_des = std::make_shared<vision_utils::DescriptorParamsORB>();
-
- params_des->nfeatures = 500; // The maximum number of features to retain.
- params_des->scaleFactor = 2; // Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor will mean that to cover certain scale range you will need more pyramid levels and so the speed will suffer.
- params_des->nlevels = 8; // The number of pyramid levels. The smallest level will have linear size equal to input_image_linear_size/pow(scaleFactor, nlevels).
- params_des->edgeThreshold = 16; // This is size of the border where the features are not detected. It should roughly match the patchSize parameter.
- params_des->firstLevel = 0; // It should be 0 in the current implementation.
- params_des->WTA_K = 2; // The number of points that produce each element of the oriented BRIEF descriptor. The default value 2 means the BRIEF where we take a random point pair and compare their brightnesses, so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3 random points (of course, those point coordinates are random, but they are generated from the pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such output will occupy 2 bits, and therefore it will need a special variant of Hamming distance, denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).
- params_des->scoreType = cv::ORB::HARRIS_SCORE; //#enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };
- params_des->patchSize = 31;
-
- vision_utils::DescriptorBasePtr des_b_ptr = vision_utils::setupDescriptor("ORB", "ORB descriptor", params_des);
- vision_utils::DescriptorORBPtr des_ptr = std::static_pointer_cast<vision_utils::DescriptorORB>(des_b_ptr);
-
- // Matcher
- vision_utils::MatcherParamsBRUTEFORCE_HAMMING_2Ptr params_mat = std::make_shared<vision_utils::MatcherParamsBRUTEFORCE_HAMMING_2>();
- vision_utils::MatcherBasePtr mat_b_ptr = vision_utils::setupMatcher("BRUTEFORCE_HAMMING_2", "BRUTEFORCE_HAMMING_2 matcher", params_mat);
- vision_utils::MatcherBRUTEFORCE_HAMMING_2Ptr mat_ptr = std::static_pointer_cast<vision_utils::MatcherBRUTEFORCE_HAMMING_2>(mat_b_ptr);
-
- //=====================================================
-
- unsigned int buffer_size = 8;
- vision_utils::Buffer<vision_utils::FramePtr> frame_buff(buffer_size);
- frame_buff.add( vision_utils::setFrame(sen_ptr->getImage(), 0) );
-
- unsigned int img_width = frame_buff.back()->getImage().cols;
- unsigned int img_height = frame_buff.back()->getImage().rows;
- std::cout << "Image size: " << img_width << "x" << img_height << std::endl;
-
- cv::namedWindow("Feature tracker"); // Creates a window for display.
- cv::moveWindow("Feature tracker", 0, 0);
- cv::startWindowThread();
- cv::imshow("Feature tracker", frame_buff.back()->getImage());
- cv::waitKey(1);
-
- KeyPointVector target_keypoints;
- KeyPointVector tracked_keypoints_;
- KeyPointVector tracked_keypoints_2;
- KeyPointVector current_keypoints;
- cv::Mat target_descriptors;
- cv::Mat tracked_descriptors;
- cv::Mat tracked_descriptors2;
- cv::Mat current_descriptors;
- cv::Mat image_original = frame_buff.back()->getImage();
- cv::Mat image_graphics;
-
- unsigned int roi_width = 200;
- unsigned int roi_heigth = 200;
-
- int n_first_1 = 0;
- int n_second_1 = 0;
-
- // Initial detection
- target_keypoints = det_ptr->detect(image_original);
- target_descriptors = des_ptr->getDescriptor(image_original, target_keypoints);
-
- for (unsigned int f_num=0; f_num < 1000; ++f_num)
- {
- frame_buff.add( vision_utils::setFrame(sen_ptr->getImage(), f_num) );
-
- KeyPointVector keypoints;
- cv::Mat descriptors;
- DMatchVector cv_matches;
- cv::Mat image = frame_buff.back()->getImage();
- image_graphics = image.clone();
- bool matched = false;
- n_first_1 = n_second_1 = 0;
-
- unsigned int tracked_keypoints = 0;
-
- for(unsigned int target_idx = 0; target_idx < target_keypoints.size(); target_idx++)
- {
- std::cout << "\npixel: " << target_keypoints[target_idx].pt << std::endl;
- std::cout << "target_descriptor[" << target_idx << "]:\n" << target_descriptors.row(target_idx) << std::endl;
-
- matched = false;
-
- cv::Rect roi = vision_utils::setRoi(target_keypoints[target_idx].pt.x, target_keypoints[target_idx].pt.y, roi_width, roi_heigth);
-
- cv::Point2f roi_up_left_corner;
- roi_up_left_corner.x = roi.x;
- roi_up_left_corner.y = roi.y;
-
- for(unsigned int fr = 0; fr < 2; fr++)
- {
- keypoints = det_ptr->detect(image, roi);
- descriptors = des_ptr->getDescriptor(image, keypoints);
-
- cv::Mat target_descriptor; //B(cv::Rect(0,0,vec_length,1));
- target_descriptor = target_descriptors(cv::Rect(0,target_idx,target_descriptors.cols,1));
-
- if(keypoints.size() != 0)
- {
- mat_ptr->match(target_descriptor, descriptors, des_ptr->getSize(), cv_matches);
- Scalar normalized_score = 1 - (Scalar)(cv_matches[0].distance)/(des_ptr->getSize()*8);
- std::cout << "pixel: " << keypoints[cv_matches[0].trainIdx].pt + roi_up_left_corner << std::endl;
- std::cout << "normalized score: " << normalized_score << std::endl;
- if(normalized_score < 0.8)
- {
- std::cout << "not tracked" << std::endl;
- }
- else
- {
- std::cout << "tracked" << std::endl;
-
- matched = true;
-
- cv::Point2f point,t_point;
- point.x = keypoints[cv_matches[0].trainIdx].pt.x;
- point.y = keypoints[cv_matches[0].trainIdx].pt.y;
- t_point.x = target_keypoints[target_idx].pt.x;
- t_point.y = target_keypoints[target_idx].pt.y;
-
- cv::circle(image_graphics, t_point, 4, cv::Scalar(51.0, 51.0, 255.0), -1, 3, 0);
- cv::circle(image_graphics, point, 2, cv::Scalar(255.0, 255.0, 0.0), -1, 8, 0);
- cv::putText(image_graphics, std::to_string(target_idx), point, cv:: FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(255.0, 255.0, 0.0));
-
- //introduce in list - tracked point
- cv::KeyPoint tracked_kp = keypoints[cv_matches[0].trainIdx];
- tracked_kp.pt.x = tracked_kp.pt.x + roi.x;
- tracked_kp.pt.y = tracked_kp.pt.y + roi.y;
- if(fr==0)
- tracked_keypoints_.push_back(tracked_kp);
- else
- tracked_keypoints_2.push_back(tracked_kp);
-
- cv::Mat tracked_desc;
- tracked_desc = descriptors(cv::Rect(0,cv_matches[0].trainIdx,target_descriptors.cols,1));
- if(fr==0)
- tracked_descriptors.push_back(tracked_desc);
- else
- tracked_descriptors2.push_back(tracked_desc);
-
- //introduce in list - target point
- if(fr==0)
- {
- current_keypoints.push_back(target_keypoints[target_idx]);
- current_descriptors.push_back(target_descriptor);
- }
-
- if (fr == 0 && normalized_score == 1)n_first_1++;
- if (fr == 1 && normalized_score == 1)n_second_1++;
- }
- }
- else
- std::cout << "not tracked" << std::endl;
-
- }
- if (matched) tracked_keypoints++;
- }
-
- std::cout << "\ntracked keypoints: " << tracked_keypoints << "/" << target_keypoints.size() << std::endl;
- std::cout << "percentage first: " << ((float)((float)tracked_keypoints/(float)target_keypoints.size()))*100 << "%" << std::endl;
- std::cout << "Number of perfect first matches: " << n_first_1 << std::endl;
- std::cout << "Number of perfect second matches: " << n_second_1 << std::endl;
-
- if(tracked_keypoints == 0)
- {
- target_keypoints = det_ptr->detect(image);
- target_descriptors = des_ptr->getDescriptor(image, target_keypoints);
- std::cout << "number of new keypoints to be tracked: " << target_keypoints.size() << std::endl;
- }
- else
- {
- std::cout << "\n\nADVANCE" << std::endl;
-// for(unsigned int i = 0; i < target_keypoints.size(); i++)
-// {
-// std::cout << "\ntarget keypoints";
-// std::cout << target_keypoints[i].pt;
-// }
-// for(unsigned int i = 0; i < current_keypoints.size(); i++)
-// {
-// std::cout << "\ncurrent keypoints";
-// std::cout << current_keypoints[i].pt;
-// }
-// for( int i = 0; i < target_descriptors.rows; i++)
-// {
-// std::cout << "\ntarget descriptors";
-// std::cout << target_descriptors.row(i);
-// }
-// for( int i = 0; i < current_descriptors.rows; i++)
-// {
-// std::cout << "\ncurrent descriptors";
-// std::cout << current_descriptors.row(i);
-// }
-// for( int i = 0; i < current_descriptors2.rows; i++)
-// {
-// std::cout << "\ncurrent descriptors2";
-// std::cout << current_descriptors2.row(i);
-// }
-
- //target_keypoints.clear();
- target_keypoints = current_keypoints;
- current_descriptors.copyTo(target_descriptors);
- current_keypoints.clear();
- current_descriptors.release();
-
- std::cout << "\nAFTER THE ADVANCE" << std::endl;
-// for(unsigned int i = 0; i < target_keypoints.size(); i++)
-// {
-// std::cout << "target keypoints";
-// std::cout << target_keypoints[i].pt << "\t" ;
-// }
-// for( int i = 0; i < target_descriptors.rows; i++)
-// {
-// std::cout << "\ntarget descriptors";
-// std::cout << target_descriptors.row(i);
-// }
-
- std::cout << "\nEND OF ADVANCE\n";
-
- }
-
- tracked_keypoints = 0;
- cv::imshow("Feature tracker", image_graphics);
- cv::waitKey(1);
- }
-}
diff --git a/demos/demo_virtual_hierarchy.cpp b/demos/demo_virtual_hierarchy.cpp
deleted file mode 100644
index fb1b248ce..000000000
--- a/demos/demo_virtual_hierarchy.cpp
+++ /dev/null
@@ -1,354 +0,0 @@
-/*
- * test_virtual_hierarchy.cpp
- *
- * Created on: Sep 8, 2014
- * Author: jsola
- */
-
-#include <list>
-
-namespace wolf{
-
-// BASE CLASSES
-
-/**
- * \brief Node class.
- *
- * The Node class has only an ID and an ID factory built in the constructor.
- */
-class N
-{
- private:
- unsigned int id_;
- static unsigned int id_count_;
- protected:
- N() : id_(++id_count_) { }
- virtual ~N() { }
- public:
- unsigned int id() { return id_; }
-};
-
-/**
- * \brief Base class for children.
- *
- * It has a pointer to parent.
- *
- * NOTE: The virtual inheritance solves the "diamond of death" problem.
- */
-template<class Parent>
-class ChildOf : virtual public N
-{
- private:
- Parent* up_ptr_;
- protected:
- ChildOf(Parent* _up_ptr) : up_ptr_(_up_ptr) { }
- virtual ~ChildOf() { }
- Parent* up() { return up_ptr_; }
-};
-
-/**
- * \brief Base class for parents
- *
- * It has a list of pointers to children, and a dumy method 'print' that is recursive to all children.
- *
- * NOTE: The virtual inheritance solves the "diamond of death" problem.
- */
-template<class Child>
-class ParentOf : virtual public N
-{
- private:
- std::list<Child*> down_list_;
- protected:
- ParentOf() { }
- virtual ~ParentOf() { }
- public:
- void addToList(Child* _down_ptr) { down_list_.push_back(_down_ptr); }
- std::list<Child*> downList() { return down_list_; }
- virtual void print();
-};
-
-///*
-// * Virtual inheritance solves the "diamond of death" problem.
-// */
-//template<class Sibling>
-//class SiblingOf : virtual public N
-//{
-// private:
-// std::list<Sibling*> side_list_;
-// protected:
-// SiblingOf() { }
-// virtual ~SiblingOf() { }
-// public:
-// void addToList(Sibling* _side_ptr) { side_list_.push_back(_side_ptr); }
-// std::list<Sibling*> sideList() { return side_list_; }
-//};
-
-/**
- * \brief Base class for bottom nodes.
- *
- * This class is for children that are no parents - they are bottom nodes
- *
- * It overloads the dummy 'print' function so that this is is not recursive any more.
- *
- * NOTE: The virtual inheritance solves the "diamond of death" problem.
- */
-class Bot : virtual public N
-{
- protected:
- virtual ~Bot() { }
- public:
- virtual void print();
-};
-
-//template<class Child>
-//class ExplorerOf : public ParentOf<Child>
-//{
-// protected:
-// ExplorerOf() { }
-// virtual ~ExplorerOf() { }
-// public:
-// virtual void explore();
-//};
-
-//class Explored : public Bot
-//{
-// protected:
-// virtual ~Explored() { }
-// public:
-// virtual void explore() { }
-//};
-
-// DERIVED ISOLATED CLASSES
-
-// a bunch of fwd_decs
-class VehNode;
-class FrmNode;
-class CapNode;
-class FeaNode;
-class CorNode;
-class TrSNode;
-class SenNode;
-
-class Veh
-{
- public:
- Veh() : v_(1){}
- void duplicate(){v_ *= 2;}
- double v(){return v_;}
- private:
- double v_;
-};
-class Frm
-{
- public:
- Frm() : f_(1){}
- void duplicate(){f_ *= 2;}
- double f(){return f_;}
- private:
- double f_;
-};
-class Cap
-{
- public:
- Cap() : c_(1){}
- void duplicate(){c_ *= 2;}
- double c(){return c_;}
- private:
- double c_;
-};
-class Fea
-{
- public:
- Fea() : ft_(1){}
- void duplicate(){ft_ *= 2;}
- double ft(){return ft_;}
- private:
- double ft_;
-};
-class Cor
-{
-public:
- Cor() : co_(1){}
- void duplicate(){co_ *= 2;}
- double co(){return co_;}
-private:
- double co_;
-};
-class Sen
-{
- public:
- Sen() : s_(1){}
- void duplicate(){s_ *= 2;}
- double s(){return s_;}
- private:
- double s_;
-};
-
-// Derived classes for all levels of the tree
-
-class VehNode : public Veh, public ParentOf<FrmNode>, public ParentOf<SenNode>
-{
- public:
- VehNode() { }
- virtual ~VehNode() { }
- void print(); // Overload because I am Top and have both Down and Explorer children.
-};
-class FrmNode : public Frm, public ChildOf<VehNode>, public ParentOf<CapNode>
-{
- public:
- FrmNode(VehNode* _veh_ptr) : ChildOf<VehNode>(_veh_ptr) { }
- virtual ~FrmNode() { }
-};
-class CapNode : public Cap, public ChildOf<FrmNode>, public ParentOf<FeaNode>//, public SiblingOf<TrSNode>
-{
- public:
- CapNode(FrmNode* _frm_ptr) : ChildOf<FrmNode>(_frm_ptr) { }
- virtual ~CapNode() { }
- void explore(); // Overload because I have both Explorer and Side children
-};
-class FeaNode : public Fea, public ChildOf<CapNode>, public ParentOf<CorNode>
-{
- public:
- FeaNode(CapNode* _cap_ptr) : ChildOf<CapNode>(_cap_ptr) { }
- virtual ~FeaNode() { }
-};
-class CorNode : public Cor, public ChildOf<FeaNode>, public Bot//, public Explored
-{
- public:
- CorNode(FeaNode* _fea_ptr) : ChildOf<FeaNode>(_fea_ptr) { }
- virtual ~CorNode() { }
-};
-//class TrSNode : public virtual N
-//{
-// public:
-// TrSNode() { }
-// virtual ~TrSNode() { }
-//};
-class SenNode : public Sen, public ChildOf<VehNode>, public Bot
-{
- public:
- SenNode(VehNode* _veh_ptr) : ChildOf<VehNode>(_veh_ptr) { }
- virtual ~SenNode() { }
-};
-
-} // namespace wolf
-
-/////////////////////
-// IMPLEMENTATIONS, here to avoid incomplete types and unwanted #includes
-/////////////////////
-
-#include <iostream>
-
-namespace wolf {
-using namespace std;
-
-template<class Child>
-void ParentOf<Child>::print()
-{
- cout << this->id() << ":( ";
- for (auto const & it_ptr : this->downList())
- cout << it_ptr->id() << " ";
- cout << ")" << endl;
- for (auto const & it_ptr : this->downList())
- it_ptr->print();
-}
-
-//template<class Child>
-//void ExplorerOf<Child>::explore()
-//{
-// cout << this->id() << ":( "; // Yes I look sad but I'm OK.
-// for (auto const & it_ptr : ParentOf<Child>::downList())
-// cout << it_ptr->id() << " ";
-// cout << ")" << endl;
-// for (auto const & it_ptr : ParentOf<Child>::downList())
-// it_ptr->explore();
-//}
-
-void Bot::print(){
- cout << this->id() << ":( Bottom )" << endl;
-}
-
-void VehNode::print()
-{
- cout << "Vehicle Own Field: v_ = " << v() << endl;
- cout << "Vehicle Hardware:" << endl;
- ParentOf < SenNode > ::print();
- cout << "Vehicle Data:" << endl;
- ParentOf < FrmNode > ::print();
-}
-
-//void CapNode::explore()
-//{
-// cout << this->id() << ":( "; // Yes I look sad but I'm OK.
-// for (auto const & it_ptr : ExplorerOf<FeaNode>::downList())
-// cout << it_ptr->id() << " ";
-// cout << "/ ";
-// for (auto const & it_ptr : SiblingOf<TrSNode>::sideList())
-// cout << it_ptr->id() << " ";
-// cout << ")" << endl;
-// for (auto const & it_ptr : ExplorerOf<FeaNode>::downList())
-// it_ptr->explore();
-//}
-
-///////////////////////
-// START APPLICATION
-///////////////////////
-
-unsigned int N::id_count_ = 0;
-
-} // namespace wolf
-
-int main()
-{
- using namespace wolf;
-
- // Create all nodes with up-pointers already set up
- VehNode V;
- SenNode S0(&V), S1(&V);
- FrmNode F0(&V), F1(&V);
- CapNode C00(&F0), C01(&F0), C10(&F1), C11(&F1);
- FeaNode f000(&C00), f001(&C00), f010(&C01), f011(&C01), f100(&C10), f101(&C10), f110(&C11), f111(&C11);
-// TrSNode T0001, T0010, T0011, T0110, T0111, T1011;
-
- // Add sensors to vehicle
- V.ParentOf < SenNode > ::addToList(&S0);
- V.ParentOf < SenNode > ::addToList(&S1);
-
- // Add frames to vehicle
- V.ParentOf < FrmNode > ::addToList(&F0);
- V.ParentOf < FrmNode > ::addToList(&F1);
-
- // Add captures to frames
- F0.ParentOf<CapNode>::addToList(&C00);
- F0.ParentOf<CapNode>::addToList(&C01);
- F1.ParentOf<CapNode>::addToList(&C10);
- F1.ParentOf<CapNode>::addToList(&C11);
-
- // Add features to captures
- C00.ParentOf<FeaNode>::addToList(&f000);
- C00.ParentOf<FeaNode>::addToList(&f001);
- C01.ParentOf<FeaNode>::addToList(&f010);
- C01.ParentOf<FeaNode>::addToList(&f011);
- C10.ParentOf<FeaNode>::addToList(&f100);
- C10.ParentOf<FeaNode>::addToList(&f101);
- C11.ParentOf<FeaNode>::addToList(&f110);
- C11.ParentOf<FeaNode>::addToList(&f111);
-
-// // Add trans-sensors to captures
-// C00.SiblingOf<TrSNode>::addToList(&T0001);
-// C00.SiblingOf<TrSNode>::addToList(&T0010);
-// C00.SiblingOf<TrSNode>::addToList(&T0011);
-// C01.SiblingOf<TrSNode>::addToList(&T0110);
-// C01.SiblingOf<TrSNode>::addToList(&T0111);
-// C10.SiblingOf<TrSNode>::addToList(&T1011);
-
- // explore() : means we are calling advanced functionality from Explorer classes. Here, we just fake.
- // print() : means we just print linkage info.
- cout << "V.explore():" << endl;
-// V.explore();
- V.duplicate();
- cout << "V.print():" << endl;
- V.print();
-
- return 0;
-}
diff --git a/demos/demo_wolf_autodiffwrapper.cpp b/demos/demo_wolf_autodiffwrapper.cpp
deleted file mode 100644
index 8d0897956..000000000
--- a/demos/demo_wolf_autodiffwrapper.cpp
+++ /dev/null
@@ -1,316 +0,0 @@
-// Testing creating wolf tree from imported .graph file
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-//std includes
-#include <iostream>
-#include <memory>
-#include <random>
-#include <cmath>
-#include <queue>
-
-//Wolf includes
-#include "wolf_manager.h"
-#include "core/capture/capture_void.h"
-#include "core/ceres_wrapper/ceres_manager.h"
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- //Welcome message
- std::cout << std::endl << " ========= WOLF IMPORTED .graph TEST ===========" << std::endl << std::endl;
-
- if (argc != 3 || atoi(argv[2]) < 0 )
- {
- std::cout << "Please call me with: [./test_wolf_imported_graph FILE_PATH MAX_VERTICES], where:" << std::endl;
- std::cout << " FILE_PATH is the .graph file path" << std::endl;
- std::cout << " MAX_VERTICES max edges to be loaded (0: ALL)" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
-
- // auxiliar variables
- std::string file_path_ = argv[1];
- unsigned int MAX_VERTEX = atoi(argv[2]);
- if (MAX_VERTEX == 0) MAX_VERTEX = 1e6;
- std::ifstream offLineFile_;
- clock_t t1;
- ceres::Solver::Summary summary_ceres_diff, summary_wolf_diff;
-
- // loading variables
- std::map<unsigned int, FrameBasePtr> index_2_frame_ptr_ceres_diff;
- std::map<unsigned int, FrameBasePtr> index_2_frame_ptr_wolf_diff;
- std::map<FrameBasePtr, unsigned int> frame_ptr_2_index_wolf_diff;
-
- // Wolf problem
- ProblemPtr wolf_problem_ceres_diff = new Problem(FRM_PO_2D);
- ProblemPtr wolf_problem_wolf_diff = new Problem(FRM_PO_2D);
- SensorBasePtr sensor = new SensorBase("ODOM 2D", std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), std::make_shared<StateBlock>(Eigen::VectorXs::Zero(1)), std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), 2);
-
- // Ceres wrappers
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- ceres_options.max_num_iterations = 1e4;
- CeresManager* ceres_manager_ceres_diff = new CeresManager(wolf_problem_ceres_diff, ceres_options, false);
- CeresManager* ceres_manager_wolf_diff = new CeresManager(wolf_problem_wolf_diff, ceres_options, true);
-
- // load graph from .txt
- offLineFile_.open(file_path_.c_str(), std::ifstream::in);
- if (offLineFile_.is_open())
- {
- std::string buffer;
- unsigned int j = 0;
- // Line by line
- while (std::getline(offLineFile_, buffer))
- {
- //std::cout << "new line:" << buffer << std::endl;
- std::string bNum;
- unsigned int i = 0;
-
- // VERTEX
- if (buffer.at(0) == 'V')
- {
- //skip rest of VERTEX word
- while (buffer.at(i) != ' ') i++;
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //vertex index
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int vertex_index = atoi(bNum.c_str());
- bNum.clear();
-
- if (vertex_index <= MAX_VERTEX+1)
- {
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // vertex pose
- Eigen::Vector3s vertex_pose;
- // x
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // y
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // theta
- while (i < buffer.size() && buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(2) = atof(bNum.c_str());
- bNum.clear();
-
- // add frame to problem
- FrameBasePtr vertex_frame_ptr_ceres_diff = new FrameBase(TimeStamp(0), std::make_shared<StateBlock>(vertex_pose.head(2)), std::make_shared<StateBlock>(vertex_pose.tail(1)));
- FrameBasePtr vertex_frame_ptr_wolf_diff = new FrameBase(TimeStamp(0), std::make_shared<StateBlock>(vertex_pose.head(2)), std::make_shared<StateBlock>(vertex_pose.tail(1)));
- wolf_problem_ceres_diff->getTrajectory()->addFrame(vertex_frame_ptr_ceres_diff);
- wolf_problem_wolf_diff->getTrajectory()->addFrame(vertex_frame_ptr_wolf_diff);
- // store
- index_2_frame_ptr_ceres_diff[vertex_index] = vertex_frame_ptr_ceres_diff;
- index_2_frame_ptr_wolf_diff[vertex_index] = vertex_frame_ptr_wolf_diff;
- frame_ptr_2_index_wolf_diff[vertex_frame_ptr_wolf_diff] = vertex_index;
-
- //std::cout << "Added vertex! index: " << vertex_index << " id: " << vertex_frame_ptr_wolf_diff->id() << std::endl << "pose: " << vertex_pose.transpose() << std::endl;
- }
- }
- // EDGE
- else if (buffer.at(0) == 'E')
- {
- j++;
- //skip rest of EDGE word
- while (buffer.at(i) != ' ') i++;
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //from
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int edge_old = atoi(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //to index
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int edge_new = atoi(bNum.c_str());
- bNum.clear();
-
- if (edge_new <= MAX_VERTEX+1 && edge_old <= MAX_VERTEX+1 )
- {
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // edge vector
- Eigen::Vector3s edge_vector;
- // x
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // y
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // theta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(2) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // edge covariance
- Eigen::Matrix3s edge_information;
- // xx
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // xy
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,1) = atof(bNum.c_str());
- edge_information(1,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // yy
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(1,1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // thetatheta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(2,2) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // xtheta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,2) = atof(bNum.c_str());
- edge_information(2,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // ytheta
- while (i < buffer.size() && buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(1,2) = atof(bNum.c_str());
- edge_information(2,1) = atof(bNum.c_str());
- bNum.clear();
-
- // add capture, feature and factor to problem
- FeatureBasePtr feature_ptr_ceres_diff = new FeatureBase("POSE", edge_vector, edge_information.inverse());
- FeatureBasePtr feature_ptr_wolf_diff = new FeatureBase("POSE", edge_vector, edge_information.inverse());
- CaptureVoid* capture_ptr_ceres_diff = new CaptureVoid(TimeStamp(0), sensor);
- CaptureVoid* capture_ptr_wolf_diff = new CaptureVoid(TimeStamp(0), sensor);
- assert(index_2_frame_ptr_ceres_diff.find(edge_old) != index_2_frame_ptr_ceres_diff.end() && "edge from vertex not added!");
- assert(index_2_frame_ptr_wolf_diff.find(edge_old) != index_2_frame_ptr_wolf_diff.end() && "edge from vertex not added!");
- FrameBasePtr frame_old_ptr_ceres_diff = index_2_frame_ptr_ceres_diff[edge_old];
- FrameBasePtr frame_old_ptr_wolf_diff = index_2_frame_ptr_wolf_diff[edge_old];
- assert(index_2_frame_ptr_ceres_diff.find(edge_new) != index_2_frame_ptr_ceres_diff.end() && "edge to vertex not added!");
- assert(index_2_frame_ptr_wolf_diff.find(edge_new) != index_2_frame_ptr_wolf_diff.end() && "edge to vertex not added!");
- FrameBasePtr frame_new_ptr_ceres_diff = index_2_frame_ptr_ceres_diff[edge_new];
- FrameBasePtr frame_new_ptr_wolf_diff = index_2_frame_ptr_wolf_diff[edge_new];
- frame_new_ptr_ceres_diff->addCapture(capture_ptr_ceres_diff);
- frame_new_ptr_wolf_diff->addCapture(capture_ptr_wolf_diff);
- capture_ptr_ceres_diff->addFeature(feature_ptr_ceres_diff);
- capture_ptr_wolf_diff->addFeature(feature_ptr_wolf_diff);
- FactorOdom2D* factor_ptr_ceres_diff = new FactorOdom2D(feature_ptr_ceres_diff, frame_old_ptr_ceres_diff);
- FactorOdom2D* factor_ptr_wolf_diff = new FactorOdom2D(feature_ptr_wolf_diff, frame_old_ptr_wolf_diff);
- feature_ptr_ceres_diff->addFactor(factor_ptr_ceres_diff);
- feature_ptr_wolf_diff->addFactor(factor_ptr_wolf_diff);
- //std::cout << "Added edge! " << factor_ptr_wolf_diff->id() << " from vertex " << factor_ptr_wolf_diff->getCapture()->getFrame()->id() << " to " << factor_ptr_wolf_diff->getFrameTo()->id() << std::endl;
- //std::cout << "vector " << factor_ptr_wolf_diff->getMeasurement().transpose() << std::endl;
- //std::cout << "information " << std::endl << edge_information << std::endl;
- //std::cout << "covariance " << std::endl << factor_ptr_wolf_diff->getMeasurementCovariance() << std::endl;
- }
- }
- else
- assert("unknown line");
- }
- printf("\nGraph loaded!\n");
- }
- else
- printf("\nError opening file\n");
-
- // PRIOR
- FrameBasePtr first_frame_ceres_diff = wolf_problem_ceres_diff->getTrajectory()->getFrameList().front();
- FrameBasePtr first_frame_wolf_diff = wolf_problem_wolf_diff->getTrajectory()->getFrameList().front();
- CaptureFix* initial_covariance_ceres_diff = new CaptureFix(TimeStamp(0), new SensorBase("ABSOLUTE POSE", nullptr, nullptr, nullptr, 0), first_frame_ceres_diff->getState(), Eigen::Matrix3s::Identity() * 0.01);
- CaptureFix* initial_covariance_wolf_diff = new CaptureFix(TimeStamp(0), new SensorBase("ABSOLUTE POSE", nullptr, nullptr, nullptr, 0), first_frame_wolf_diff->getState(), Eigen::Matrix3s::Identity() * 0.01);
- first_frame_ceres_diff->addCapture(initial_covariance_ceres_diff);
- first_frame_wolf_diff->addCapture(initial_covariance_wolf_diff);
- initial_covariance_ceres_diff->process();
- initial_covariance_wolf_diff->process();
- //std::cout << "initial covariance: factor " << initial_covariance_wolf_diff->getFeatureList().front()->getFactorFromList().front()->id() << std::endl << initial_covariance_wolf_diff->getFeatureList().front()->getMeasurementCovariance() << std::endl;
-
- // COMPUTE COVARIANCES
- std::cout << "computing covariances..." << std::endl;
- t1 = clock();
- ceres_manager_ceres_diff->computeCovariances(ALL);//ALL_MARGINALS
- double t_sigma_ceres = ((double) clock() - t1) / CLOCKS_PER_SEC;
- t1 = clock();
- ceres_manager_wolf_diff->computeCovariances(ALL);//ALL_MARGINALS
- double t_sigma_wolf = ((double) clock() - t1) / CLOCKS_PER_SEC;
- std::cout << "computed!" << std::endl;
-
- // SOLVING PROBLEMS
- std::cout << "solving..." << std::endl;
- Eigen::VectorXs prev_ceres_state = wolf_problem_ceres_diff->getTrajectory()->getFrameList().back()->getState();
- summary_ceres_diff = ceres_manager_ceres_diff->solve();
- Eigen::VectorXs post_ceres_state = wolf_problem_ceres_diff->getTrajectory()->getFrameList().back()->getState();
- //std::cout << summary_ceres_diff.BriefReport() << std::endl;
- Eigen::VectorXs prev_wolf_state = wolf_problem_wolf_diff->getTrajectory()->getFrameList().back()->getState();
- summary_wolf_diff = ceres_manager_wolf_diff->solve();
- Eigen::VectorXs post_wolf_state = wolf_problem_wolf_diff->getTrajectory()->getFrameList().back()->getState();
- //std::cout << summary_wolf_diff.BriefReport() << std::endl;
- std::cout << "solved!" << std::endl;
-
- std::cout << "CERES AUTODIFF:" << std::endl;
- std::cout << "Covariance computation: " << t_sigma_ceres << "s" << std::endl;
- std::cout << "Solving: " << summary_ceres_diff.total_time_in_seconds << "s" << std::endl;
- std::cout << "Prev: " << prev_ceres_state.transpose() << std::endl;
- std::cout << "Post: " << post_ceres_state.transpose() << std::endl;
-
- std::cout << std::endl << "WOLF AUTODIFF:" << std::endl;
- std::cout << "Covariance computation: " << t_sigma_wolf << "s" << std::endl;
- std::cout << "Solving: " << summary_wolf_diff.total_time_in_seconds << "s" << std::endl;
- std::cout << "Prev: " << prev_wolf_state.transpose() << std::endl;
- std::cout << "Post: " << post_wolf_state.transpose() << std::endl;
-
- delete wolf_problem_ceres_diff; //not necessary to delete anything more, wolf will do it!
- delete wolf_problem_wolf_diff; //not necessary to delete anything more, wolf will do it!
- std::cout << "wolf_problem_ deleted!" << std::endl;
- delete ceres_manager_ceres_diff;
- delete ceres_manager_wolf_diff;
- std::cout << "ceres_manager deleted!" << std::endl;
- //End message
- std::cout << " =========================== END ===============================" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_wolf_factories.cpp b/demos/demo_wolf_factories.cpp
deleted file mode 100644
index b608bb958..000000000
--- a/demos/demo_wolf_factories.cpp
+++ /dev/null
@@ -1,107 +0,0 @@
-/**
- * \file test_wolf_factories.cpp
- *
- * Created on: Apr 25, 2016
- * \author: jsola
- */
-
-#include "base/processor/processor_IMU.h"
-#include "base/sensor/sensor_GPS_fix.h"
-#include "base/hardware/hardware_base.h"
-#include "base/sensor/sensor_camera.h"
-#include "base/sensor/sensor_odom_2D.h"
-#include "../sensor_imu.h"
-//#include "../sensor_gps.h"
-
-#include "base/processor/processor_odom_2D.h"
-#include "base/processor/processor_odom_3D.h"
-#include "../processor_image_feature.h"
-
-#include "base/problem/problem.h"
-
-#include "base/common/factory.h"
-
-#include <iostream>
-#include <iomanip>
-#include <cstdlib>
-
-int main(void)
-{
- using namespace wolf;
- using namespace std;
- using std::shared_ptr;
- using std::make_shared;
- using std::static_pointer_cast;
-
- //==============================================================================================
- std::string wolf_root = _WOLF_ROOT_DIR;
- std::string wolf_config = wolf_root + "/src/examples";
- std::cout << "\nwolf directory for configuration files: " << wolf_config << std::endl;
- //==============================================================================================
-
- cout << "\n====== Registering creators in the Wolf Factories =======" << endl;
-
- cout << "If you look above, you see the registered creators.\n"
- "There is only one attempt per class, and it is successful!\n"
- "We do this by registering in the class\'s .cpp file.\n"
- "\n"
- "- See \'" << wolf_root << "/src/examples/test_wolf_factories.cpp\'\n"
- " for the way to install sensors and processors to wolf::Problem." << endl;
-
- // Start creating the problem
-
- ProblemPtr problem = Problem::create(FRM_PO_3D);
-
- // define some useful parameters
- Eigen::VectorXs pq_3d(7), po_2d(3), p_3d(3);
- shared_ptr<IntrinsicsOdom2D> intr_odom2d_ptr = nullptr;
-
- cout << "\n================== Intrinsics Factory ===================" << endl;
-
- // Use params factory for camera intrinsics
- IntrinsicsBasePtr intr_cam_ptr = IntrinsicsFactory::get().create("CAMERA", wolf_config + "/camera_params_ueye_sim.yaml");
- ProcessorParamsBasePtr params_ptr = ProcessorParamsFactory::get().create("IMAGE FEATURE", wolf_config + "/processor_image_feature.yaml");
-
- cout << "CAMERA with intrinsics : " << (static_pointer_cast<IntrinsicsCamera>(intr_cam_ptr))->pinhole_model_raw.transpose() << endl;
-// cout << "Processor IMAGE image width : " << (static_pointer_cast<ProcessorParamsImage>(params_ptr))->image.width << endl;
-
- cout << "\n==================== Install Sensors ====================" << endl;
-
- // Install sensors
- problem->installSensor("CAMERA", "front left camera", pq_3d, intr_cam_ptr);
- problem->installSensor("CAMERA", "front right camera", pq_3d, wolf_config + "/camera_params_ueye_sim.yaml");
- problem->installSensor("ODOM 2D", "main odometer", po_2d, intr_odom2d_ptr);
- problem->installSensor("GPS FIX", "GPS fix", p_3d);
- problem->installSensor("IMU", "inertial", pq_3d);
-// problem->installSensor("GPS", "GPS raw", p_3d);
- problem->installSensor("ODOM 2D", "aux odometer", po_2d, intr_odom2d_ptr);
- problem->installSensor("CAMERA", "rear camera", pq_3d, wolf_root + "/src/examples/camera_params_ueye_sim.yaml");
-
- // print available sensors
- for (auto sen : problem->getHardware()->getSensorList())
- {
- cout << "Sensor " << setw(2) << left << sen->id()
- << " | type " << setw(8) << sen->getType()
- << " | name: " << sen->getName() << endl;
- }
-
- cout << "\n=================== Install Processors ===================" << endl;
-
- // Install processors and bind them to sensors -- by sensor name!
- problem->installProcessor("ODOM 2D", "main odometry", "main odometer");
- problem->installProcessor("ODOM 2D", "sec. odometry", "aux odometer");
- problem->installProcessor("IMU", "pre-integrated", "inertial");
- problem->installProcessor("IMAGE FEATURE", "ORB", "front left camera", wolf_config + "/processor_image_feature.yaml");
-// problem->createProcessor("GPS", "GPS pseudoranges", "GPS raw");
-
- // print installed processors
- for (auto sen : problem->getHardware()->getSensorList())
- for (auto prc : sen->getProcessorList())
- cout << "Processor " << setw(2) << left << prc->id()
- << " | type : " << setw(8) << prc->getType()
- << " | name: " << setw(17) << prc->getName()
- << " | bound to sensor " << setw(2) << prc->getSensor()->id() << ": " << prc->getSensor()->getName() << endl;
-
- return 0;
-}
-
diff --git a/demos/demo_wolf_imported_graph.cpp b/demos/demo_wolf_imported_graph.cpp
deleted file mode 100644
index b87d3c17e..000000000
--- a/demos/demo_wolf_imported_graph.cpp
+++ /dev/null
@@ -1,415 +0,0 @@
-// Testing creating wolf tree from imported .graph file
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-//std includes
-#include <iostream>
-#include <memory>
-#include <random>
-#include <cmath>
-#include <queue>
-
-//Wolf includes
-#include "wolf_manager.h"
-#include "core/capture/capture_void.h"
-#include "core/ceres_wrapper/ceres_manager.h"
-
-// EIGEN
-//#include <Eigen/CholmodSupport>
-
-namespace wolf{
-// inserts the sparse matrix 'ins' into the sparse matrix 'original' in the place given by 'row' and 'col' integers
-void insertSparseBlock(const Eigen::SparseMatrix<Scalar>& ins, Eigen::SparseMatrix<Scalar>& original, const unsigned int& row, const unsigned int& col)
-{
- for (int k=0; k<ins.outerSize(); ++k)
- for (Eigen::SparseMatrix<Scalar>::InnerIterator iti(ins,k); iti; ++iti)
- original.coeffRef(iti.row() + row, iti.col() + col) = iti.value();
-
- original.makeCompressed();
-}
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- //Welcome message
- std::cout << std::endl << " ========= WOLF IMPORTED .graph TEST ===========" << std::endl << std::endl;
-
- if (argc != 3 || atoi(argv[2]) < 0 )
- {
- std::cout << "Please call me with: [./test_wolf_imported_graph FILE_PATH MAX_VERTICES], where:" << std::endl;
- std::cout << " FILE_PATH is the .graph file path" << std::endl;
- std::cout << " MAX_VERTICES max edges to be loaded (0: ALL)" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
-
- // auxiliar variables
- std::string file_path_ = argv[1];
- unsigned int MAX_VERTEX = atoi(argv[2]);
- if (MAX_VERTEX == 0) MAX_VERTEX = 1e6;
- std::ifstream offLineFile_;
- clock_t t1;
- ceres::Solver::Summary summary_full, summary_prun;
- Eigen::MatrixXs Sigma_ii(3,3), Sigma_ij(3,3), Sigma_jj(3,3), Sigma_z(3,3), Ji(3,3), Jj(3,3);
- Scalar xi, yi, thi, si, ci, xj, yj;
-
- // loading variables
- std::map<unsigned int, FrameBasePtr> index_2_frame_ptr_full;
- std::map<unsigned int, FrameBasePtr> index_2_frame_ptr_prun;
- std::map<FrameBasePtr, unsigned int> frame_ptr_2_index_prun;
-
- // Wolf problem
- ProblemPtr wolf_problem_full = new Problem(FRM_PO_2D);
- ProblemPtr wolf_problem_prun = new Problem(FRM_PO_2D);
- SensorBasePtr sensor = new SensorBase("ODOM 2D", std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), std::make_shared<StateBlock>(Eigen::VectorXs::Zero(1)), std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), 2);
-
- Eigen::SparseMatrix<Scalar> Lambda(0,0);
-
- // Ceres wrapper
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- ceres_options.max_num_iterations = 1e4;
- CeresManager* ceres_manager_full = new CeresManager(wolf_problem_full, ceres_options);
- CeresManager* ceres_manager_prun = new CeresManager(wolf_problem_prun, ceres_options);
-
- // load graph from .txt
- offLineFile_.open(file_path_.c_str(), std::ifstream::in);
- if (offLineFile_.is_open())
- {
- std::string buffer;
- unsigned int j = 0;
- // Line by line
- while (std::getline(offLineFile_, buffer))
- {
- //std::cout << "new line:" << buffer << std::endl;
- std::string bNum;
- unsigned int i = 0;
-
- // VERTEX
- if (buffer.at(0) == 'V')
- {
- //skip rest of VERTEX word
- while (buffer.at(i) != ' ') i++;
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //vertex index
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int vertex_index = atoi(bNum.c_str());
- bNum.clear();
-
- if (vertex_index <= MAX_VERTEX+1)
- {
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // vertex pose
- Eigen::Vector3s vertex_pose;
- // x
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // y
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // theta
- while (i < buffer.size() && buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(2) = atof(bNum.c_str());
- bNum.clear();
-
- // add frame to problem
- FrameBasePtr vertex_frame_ptr_full = new FrameBase(KEY, TimeStamp(0), std::make_shared<StateBlock>(vertex_pose.head(2)), std::make_shared<StateBlock>(vertex_pose.tail(1)));
- FrameBasePtr vertex_frame_ptr_prun = new FrameBase(KEY, TimeStamp(0), std::make_shared<StateBlock>(vertex_pose.head(2)), std::make_shared<StateBlock>(vertex_pose.tail(1)));
- wolf_problem_full->getTrajectory()->addFrame(vertex_frame_ptr_full);
- wolf_problem_prun->getTrajectory()->addFrame(vertex_frame_ptr_prun);
- // store
- index_2_frame_ptr_full[vertex_index] = vertex_frame_ptr_full;
- index_2_frame_ptr_prun[vertex_index] = vertex_frame_ptr_prun;
- frame_ptr_2_index_prun[vertex_frame_ptr_prun] = vertex_index;
- // Information matrix
- Lambda.conservativeResize(Lambda.rows()+3,Lambda.cols()+3);
-
- //std::cout << "Added vertex! index: " << vertex_index << " id: " << vertex_frame_ptr_prun->id() << std::endl << "pose: " << vertex_pose.transpose() << std::endl;
- }
- }
- // EDGE
- else if (buffer.at(0) == 'E')
- {
- j++;
- //skip rest of EDGE word
- while (buffer.at(i) != ' ') i++;
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //from
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int edge_old = atoi(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //to index
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int edge_new = atoi(bNum.c_str());
- bNum.clear();
-
- if (edge_new <= MAX_VERTEX+1 && edge_old <= MAX_VERTEX+1 )
- {
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // edge vector
- Eigen::Vector3s edge_vector;
- // x
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // y
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // theta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(2) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // edge covariance
- Eigen::Matrix3s edge_information;
- // xx
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // xy
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,1) = atof(bNum.c_str());
- edge_information(1,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // yy
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(1,1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // thetatheta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(2,2) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // xtheta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,2) = atof(bNum.c_str());
- edge_information(2,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // ytheta
- while (i < buffer.size() && buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(1,2) = atof(bNum.c_str());
- edge_information(2,1) = atof(bNum.c_str());
- bNum.clear();
-
- // add capture, feature and factor to problem
- FeatureBasePtr feature_ptr_full = new FeatureBase("POSE", edge_vector, edge_information.inverse());
- FeatureBasePtr feature_ptr_prun = new FeatureBase("POSE", edge_vector, edge_information.inverse());
- CaptureVoid* capture_ptr_full = new CaptureVoid(TimeStamp(0), sensor);
- CaptureVoid* capture_ptr_prun = new CaptureVoid(TimeStamp(0), sensor);
- assert(index_2_frame_ptr_full.find(edge_old) != index_2_frame_ptr_full.end() && "edge from vertex not added!");
- assert(index_2_frame_ptr_prun.find(edge_old) != index_2_frame_ptr_prun.end() && "edge from vertex not added!");
- FrameBasePtr frame_old_ptr_full = index_2_frame_ptr_full[edge_old];
- FrameBasePtr frame_old_ptr_prun = index_2_frame_ptr_prun[edge_old];
- assert(index_2_frame_ptr_full.find(edge_new) != index_2_frame_ptr_full.end() && "edge to vertex not added!");
- assert(index_2_frame_ptr_prun.find(edge_new) != index_2_frame_ptr_prun.end() && "edge to vertex not added!");
- FrameBasePtr frame_new_ptr_full = index_2_frame_ptr_full[edge_new];
- FrameBasePtr frame_new_ptr_prun = index_2_frame_ptr_prun[edge_new];
- frame_new_ptr_full->addCapture(capture_ptr_full);
- frame_new_ptr_prun->addCapture(capture_ptr_prun);
- capture_ptr_full->addFeature(feature_ptr_full);
- capture_ptr_prun->addFeature(feature_ptr_prun);
- FactorOdom2D* factor_ptr_full = new FactorOdom2D(feature_ptr_full, frame_old_ptr_full);
- FactorOdom2D* factor_ptr_prun = new FactorOdom2D(feature_ptr_prun, frame_old_ptr_prun);
- feature_ptr_full->addFactor(factor_ptr_full);
- feature_ptr_prun->addFactor(factor_ptr_prun);
- //std::cout << "Added edge! " << factor_ptr_prun->id() << " from vertex " << factor_ptr_prun->getCapture()->getFrame()->id() << " to " << factor_ptr_prun->getFrameTo()->id() << std::endl;
- //std::cout << "vector " << factor_ptr_prun->getMeasurement().transpose() << std::endl;
- //std::cout << "information " << std::endl << edge_information << std::endl;
- //std::cout << "covariance " << std::endl << factor_ptr_prun->getMeasurementCovariance() << std::endl;
-
- Scalar xi = *(frame_old_ptr_prun->getP()->get());
- Scalar yi = *(frame_old_ptr_prun->getP()->get()+1);
- Scalar thi = *(frame_old_ptr_prun->getO()->get());
- Scalar si = sin(thi);
- Scalar ci = cos(thi);
- Scalar xj = *(frame_new_ptr_prun->getP()->get());
- Scalar yj = *(frame_new_ptr_prun->getP()->get()+1);
- Eigen::MatrixXs Ji(3,3), Jj(3,3);
- Ji << -ci,-si,-(xj-xi)*si+(yj-yi)*ci,
- si,-ci,-(xj-xi)*ci-(yj-yi)*si,
- 0, 0, -1;
- Jj << ci, si, 0,
- -si, ci, 0,
- 0, 0, 1;
- //std::cout << "Ji" << std::endl << Ji << std::endl;
- //std::cout << "Jj" << std::endl << Jj << std::endl;
- Eigen::SparseMatrix<Scalar> DeltaLambda(Lambda.rows(), Lambda.cols());
- insertSparseBlock((Ji.transpose() * edge_information * Ji).sparseView(), DeltaLambda, edge_old*3, edge_old*3);
- insertSparseBlock((Jj.transpose() * edge_information * Jj).sparseView(), DeltaLambda, edge_new*3, edge_new*3);
- insertSparseBlock((Ji.transpose() * edge_information * Jj).sparseView(), DeltaLambda, edge_old*3, edge_new*3);
- insertSparseBlock((Jj.transpose() * edge_information * Ji).sparseView(), DeltaLambda, edge_new*3, edge_old*3);
- Lambda = Lambda + DeltaLambda;
- }
- }
- else
- assert("unknown line");
- }
- printf("\nGraph loaded!\n");
- }
- else
- printf("\nError opening file\n");
-
- // PRIOR
- FrameBasePtr first_frame_full = wolf_problem_full->getTrajectory()->getFrameList().front();
- FrameBasePtr first_frame_prun = wolf_problem_prun->getTrajectory()->getFrameList().front();
- CaptureFix* initial_covariance_full = new CaptureFix(TimeStamp(0), new SensorBase("ABSLOUTE POSE", nullptr, nullptr, nullptr, 0), first_frame_full->getState(), Eigen::Matrix3s::Identity() * 0.01);
- CaptureFix* initial_covariance_prun = new CaptureFix(TimeStamp(0), new SensorBase("ABSLOUTE POSE", nullptr, nullptr, nullptr, 0), first_frame_prun->getState(), Eigen::Matrix3s::Identity() * 0.01);
- first_frame_full->addCapture(initial_covariance_full);
- first_frame_prun->addCapture(initial_covariance_prun);
- initial_covariance_full->process();
- initial_covariance_prun->process();
- //std::cout << "initial covariance: factor " << initial_covariance_prun->getFeatureList().front()->getFactorFromList().front()->id() << std::endl << initial_covariance_prun->getFeatureList().front()->getMeasurementCovariance() << std::endl;
- Eigen::SparseMatrix<Scalar> DeltaLambda(Lambda.rows(), Lambda.cols());
- insertSparseBlock((Eigen::Matrix3s::Identity() * 100).sparseView(), DeltaLambda, 0, 0);
- Lambda = Lambda + DeltaLambda;
-
- // COMPUTE COVARIANCES
- FactorBasePtrList factors;
- wolf_problem_prun->getTrajectory()->getFactorList(factors);
- // Manual covariance computation
- t1 = clock();
- Eigen::SimplicialLLT<Eigen::SparseMatrix<Scalar>> chol(Lambda); // performs a Cholesky factorization of A
- Eigen::MatrixXs Sigma = chol.solve(Eigen::MatrixXs::Identity(Lambda.rows(), Lambda.cols()));
- double t_sigma_manual = ((double) clock() - t1) / CLOCKS_PER_SEC;
- //std::cout << "Lambda" << std::endl << Lambda << std::endl;
- //std::cout << "Sigma" << std::endl << Sigma << std::endl;
-
- std::cout << " ceres is computing covariances..." << std::endl;
- t1 = clock();
- ceres_manager_prun->computeCovariances(ALL);//ALL_MARGINALS
- double t_sigma_ceres = ((double) clock() - t1) / CLOCKS_PER_SEC;
- std::cout << "computed!" << std::endl;
-
- t1 = clock();
-
- for (auto c_it=factors.begin(); c_it!=factors.end(); c_it++)
- {
- if ((*c_it)->getCategory() != FAC_FRAME) continue;
-
- // ii (old)
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getFrameOther()->getP(), Sigma_ii, 0, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getFrameOther()->getO(), Sigma_ii, 0, 2);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getFrameOther()->getP(), Sigma_ii, 2, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getFrameOther()->getO(), Sigma_ii, 2, 2);
-// std::cout << "Sigma_ii" << std::endl << Sigma_ii << std::endl;
-// std::cout << "Sigma(i,i)" << std::endl << Sigma.block<3,3>(frame_ptr_2_index_prun[(*c_it)->getFrameTo()]*3, frame_ptr_2_index_prun[(*c_it)->getFrameTo()]*3) << std::endl;
- // jj (new)
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getP(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_jj, 0, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getP(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_jj, 0, 2);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getO(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_jj, 2, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getO(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_jj, 2, 2);
-// std::cout << "Sigma_jj" << std::endl << Sigma_jj << std::endl;
-// std::cout << "Sigma(j,j)" << std::endl << Sigma.block<3,3>(frame_ptr_2_index_prun[(*c_it)->getCapture()->getFrame()]*3, frame_ptr_2_index_prun[(*c_it)->getCapture()->getFrame()]*3) << std::endl;
- // ij (old-new)
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_ij, 0, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_ij, 0, 2);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_ij, 2, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_ij, 2, 2);
-// std::cout << "Sigma_ij" << std::endl << Sigma_ij << std::endl;
-// std::cout << "Sigma(i,j)" << std::endl << Sigma.block<3,3>(frame_ptr_2_index_prun[(*c_it)->getFrameTo()]*3, frame_ptr_2_index_prun[(*c_it)->getCapture()->getFrame()]*3) << std::endl;
-
- //jacobian
- xi = *(*c_it)->getFrameOther()->getP()->get();
- yi = *((*c_it)->getFrameOther()->getP()->get()+1);
- thi = *(*c_it)->getFrameOther()->getO()->get();
- si = sin(thi);
- ci = cos(thi);
- xj = *(*c_it)->getCapture()->getFrame()->getP()->get();
- yj = *((*c_it)->getCapture()->getFrame()->getP()->get()+1);
-
- Ji << -ci,-si,-(xj-xi)*si+(yj-yi)*ci,
- si,-ci,-(xj-xi)*ci-(yj-yi)*si,
- 0, 0, -1;
- Jj << ci, si, 0,
- -si, ci, 0,
- 0, 0, 1;
- //std::cout << "Ji" << std::endl << Ji << std::endl;
- //std::cout << "Jj" << std::endl << Jj << std::endl;
-
- // Measurement covariance
- Sigma_z = (*c_it)->getFeature()->getMeasurementCovariance();
- //std::cout << "Sigma_z" << std::endl << Sigma_z << std::endl;
- //std::cout << "Sigma_z.determinant() = " << Sigma_z.determinant() << std::endl;
-
- //std::cout << "denominador : " << std::endl << Sigma_z - (Ji * Sigma_ii * Ji.transpose() + Jj * Sigma_jj * Jj.transpose() + Ji * Sigma_ij * Jj.transpose() + Jj * Sigma_ij.transpose() * Ji.transpose()) << std::endl;
- // Information gain
- Scalar IG = 0.5 * log( Sigma_z.determinant() / (Sigma_z - (Ji * Sigma_ii * Ji.transpose() + Jj * Sigma_jj * Jj.transpose() + Ji * Sigma_ij * Jj.transpose() + Jj * Sigma_ij.transpose() * Ji.transpose())).determinant() );
- //std::cout << "IG = " << IG << std::endl;
-
- if (IG < 2)
- (*c_it)->setStatus(FAC_INACTIVE);
- }
- double t_ig = ((double) clock() - t1) / CLOCKS_PER_SEC;
- std::cout << "manual sigma computation " << t_sigma_manual << "s" << std::endl;
- std::cout << "ceres sigma computation " << t_sigma_ceres << "s" << std::endl;
- std::cout << "information gain computation " << t_ig << "s" << std::endl;
-
- // SOLVING PROBLEMS
- std::cout << "solving..." << std::endl;
- summary_full = ceres_manager_full->solve();
- std::cout << summary_full.FullReport() << std::endl;
- summary_prun = ceres_manager_prun->solve();
- std::cout << summary_prun.FullReport() << std::endl;
-
- delete wolf_problem_full; //not necessary to delete anything more, wolf will do it!
- std::cout << "wolf_problem_ deleted!" << std::endl;
- delete ceres_manager_full;
- delete ceres_manager_prun;
- std::cout << "ceres_manager deleted!" << std::endl;
- //End message
- std::cout << " =========================== END ===============================" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_wolf_logging.cpp b/demos/demo_wolf_logging.cpp
deleted file mode 100644
index 3b7bdfab7..000000000
--- a/demos/demo_wolf_logging.cpp
+++ /dev/null
@@ -1,24 +0,0 @@
-/**
- * \file test_wolf_logging.cpp
- *
- * Created on: Oct 28, 2016
- * \author: Jeremie Deray
- */
-
-#include "base/common/wolf.h"
-#include "base/utils/logging.h"
-
-int main(int, char*[])
-{
- WOLF_INFO("test info ", 5, " ", 0.123);
-
- WOLF_WARN("test warn ", 5, " ", 0.123);
-
- WOLF_ERROR("test error ", 5, " ", 0.123);
-
- WOLF_TRACE("test trace ", 5, " ", 0.123);
-
- WOLF_DEBUG("test debug ", 5, " ", 0.123);
-
- return 0;
-}
diff --git a/demos/demo_wolf_prunning.cpp b/demos/demo_wolf_prunning.cpp
deleted file mode 100644
index 99567b5c3..000000000
--- a/demos/demo_wolf_prunning.cpp
+++ /dev/null
@@ -1,566 +0,0 @@
-// Testing creating wolf tree from imported .graph file
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-//std includes
-#include <iostream>
-#include <memory>
-#include <random>
-#include <cmath>
-#include <queue>
-
-//Wolf includes
-#include "wolf_manager.h"
-#include "core/capture/capture_void.h"
-#include "core/factor/factor_base.h"
-#include "core/ceres_wrapper/ceres_manager.h"
-
-// EIGEN
-//#include <Eigen/CholmodSupport>
-#include <Eigen/StdVector> // Eigen in std vector
-
-namespace wolf{
-// inserts the sparse matrix 'ins' into the sparse matrix 'original' in the place given by 'row' and 'col' integers
-
-void insertSparseBlock(const Eigen::SparseMatrix<Scalar>& ins, Eigen::SparseMatrix<Scalar>& original, const unsigned int& row, const unsigned int& col)
-{
- for (int k=0; k<ins.outerSize(); ++k)
- for (Eigen::SparseMatrix<Scalar>::InnerIterator iti(ins,k); iti; ++iti)
- original.coeffRef(iti.row() + row, iti.col() + col) = iti.value();
-
- original.makeCompressed();
-}
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- //Welcome message
- std::cout << std::endl << " ========= WOLF IMPORTED .graph TEST ===========" << std::endl << std::endl;
-
- if (argc != 3 || atoi(argv[2]) < 0 )
- {
- std::cout << "Please call me with: [./test_wolf_imported_graph FILE_PATH MAX_VERTICES], where:" << std::endl;
- std::cout << " FILE_PATH is the .graph file path" << std::endl;
- std::cout << " MAX_VERTICES max edges to be loaded (0: ALL)" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
-
- // auxiliar variables
- std::string file_path_ = argv[1];
- unsigned int MAX_VERTEX = atoi(argv[2]);
- if (MAX_VERTEX == 0) MAX_VERTEX = 1e6;
- std::ifstream offLineFile_;
- clock_t t1;
- ceres::Solver::Summary summary_full, summary_prun;
- Eigen::MatrixXs Sigma_ii(3,3), Sigma_ij(3,3), Sigma_jj(3,3), Sigma_z(3,3), Ji(3,3), Jj(3,3);
- Eigen::MatrixXs Sigma_11(2,2), Sigma_12(2,1), Sigma_13(2,2), Sigma_14(2,1),
- Sigma_22(1,1), Sigma_23(1,2), Sigma_24(1,1),
- Sigma_33(2,2), Sigma_34(2,1),
- Sigma_44(1,1);
-
- std::vector<Eigen::MatrixXs> jacobians;
- jacobians.push_back(Eigen::MatrixXs::Zero(3,2));
- jacobians.push_back(Eigen::MatrixXs::Zero(3,1));
- jacobians.push_back(Eigen::MatrixXs::Zero(3,2));
- jacobians.push_back(Eigen::MatrixXs::Zero(3,1));
- Scalar xi, yi, thi, si, ci, xj, yj;
- double t_sigma_manual = 0;
-
- // loading variables
- std::map<unsigned int, FrameBasePtr> index_2_frame_ptr_full;
- std::map<unsigned int, FrameBasePtr> index_2_frame_ptr_prun;
- std::map<FrameBasePtr, unsigned int> frame_ptr_2_index_prun;
-
- // Wolf problem
- ProblemPtr wolf_problem_full = new Problem(FRM_PO_2D);
- ProblemPtr wolf_problem_prun = new Problem(FRM_PO_2D);
- SensorBasePtr sensor = new SensorBase("ODOM 2D", std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), std::make_shared<StateBlock>(Eigen::VectorXs::Zero(1)), std::make_shared<StateBlock>(Eigen::VectorXs::Zero(2)), 2);
-
- Eigen::SparseMatrix<Scalar> Lambda(0,0);
-
- // prunning
- FactorBasePtrList ordered_fac_ptr;
- std::list<Scalar> ordered_ig;
-
- // Ceres wrapper
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- ceres_options.max_num_iterations = 1e4;
- CeresManager* ceres_manager_full = new CeresManager(wolf_problem_full, ceres_options);
- CeresManager* ceres_manager_prun = new CeresManager(wolf_problem_prun,ceres_options);
-
- // load graph from .txt
- offLineFile_.open(file_path_.c_str(), std::ifstream::in);
- if (offLineFile_.is_open())
- {
- std::string buffer;
- unsigned int j = 0;
- // Line by line
- while (std::getline(offLineFile_, buffer))
- {
- //std::cout << "new line:" << buffer << std::endl;
- std::string bNum;
- unsigned int i = 0;
-
- // VERTEX
- if (buffer.at(0) == 'V')
- {
- //skip rest of VERTEX word
- while (buffer.at(i) != ' ') i++;
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //vertex index
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int vertex_index = atoi(bNum.c_str());
- bNum.clear();
-
- if (vertex_index <= MAX_VERTEX+1)
- {
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // vertex pose
- Eigen::Vector3s vertex_pose;
- // x
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // y
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // theta
- while (i < buffer.size() && buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- vertex_pose(2) = atof(bNum.c_str());
- bNum.clear();
-
- // add frame to problem
- FrameBasePtr vertex_frame_ptr_full = new FrameBase(KEY, TimeStamp(0), std::make_shared<StateBlock>(vertex_pose.head(2)), std::make_shared<StateBlock>(vertex_pose.tail(1)));
- FrameBasePtr vertex_frame_ptr_prun = new FrameBase(KEY, TimeStamp(0), std::make_shared<StateBlock>(vertex_pose.head(2)), std::make_shared<StateBlock>(vertex_pose.tail(1)));
- wolf_problem_full->getTrajectory()->addFrame(vertex_frame_ptr_full);
- wolf_problem_prun->getTrajectory()->addFrame(vertex_frame_ptr_prun);
- // store
- index_2_frame_ptr_full[vertex_index] = vertex_frame_ptr_full;
- index_2_frame_ptr_prun[vertex_index] = vertex_frame_ptr_prun;
- frame_ptr_2_index_prun[vertex_frame_ptr_prun] = vertex_index;
- // Information matrix
- Lambda.conservativeResize(Lambda.rows()+3,Lambda.cols()+3);
-
- //std::cout << "Added vertex! index: " << vertex_index << " id: " << vertex_frame_ptr_prun->id() << std::endl << "pose: " << vertex_pose.transpose() << std::endl;
- }
- }
- // EDGE
- else if (buffer.at(0) == 'E')
- {
- j++;
- //skip rest of EDGE word
- while (buffer.at(i) != ' ') i++;
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //from
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int edge_old = atoi(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- //to index
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- unsigned int edge_new = atoi(bNum.c_str());
- bNum.clear();
-
- if (edge_new <= MAX_VERTEX+1 && edge_old <= MAX_VERTEX+1 )
- {
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // edge vector
- Eigen::Vector3s edge_vector;
- // x
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // y
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // theta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_vector(2) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
-
- // edge covariance
- Eigen::Matrix3s edge_information;
- // xx
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // xy
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,1) = atof(bNum.c_str());
- edge_information(1,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // yy
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(1,1) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // thetatheta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(2,2) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // xtheta
- while (buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(0,2) = atof(bNum.c_str());
- edge_information(2,0) = atof(bNum.c_str());
- bNum.clear();
- //skip white spaces
- while (buffer.at(i) == ' ') i++;
- // ytheta
- while (i < buffer.size() && buffer.at(i) != ' ')
- bNum.push_back(buffer.at(i++));
- edge_information(1,2) = atof(bNum.c_str());
- edge_information(2,1) = atof(bNum.c_str());
- bNum.clear();
-
- //std::cout << "Adding edge... " << std::endl;
- // add capture, feature and factor to problem
- FeatureBasePtr feature_ptr_full = new FeatureBase("POSE", edge_vector, edge_information.inverse());
- FeatureBasePtr feature_ptr_prun = new FeatureBase("POSE", edge_vector, edge_information.inverse());
- CaptureVoid* capture_ptr_full = new CaptureVoid(TimeStamp(0), sensor);
- CaptureVoid* capture_ptr_prun = new CaptureVoid(TimeStamp(0), sensor);
- assert(index_2_frame_ptr_full.find(edge_old) != index_2_frame_ptr_full.end() && "edge from vertex not added!");
- assert(index_2_frame_ptr_prun.find(edge_old) != index_2_frame_ptr_prun.end() && "edge from vertex not added!");
- FrameBasePtr frame_old_ptr_full = index_2_frame_ptr_full[edge_old];
- FrameBasePtr frame_old_ptr_prun = index_2_frame_ptr_prun[edge_old];
- assert(index_2_frame_ptr_full.find(edge_new) != index_2_frame_ptr_full.end() && "edge to vertex not added!");
- assert(index_2_frame_ptr_prun.find(edge_new) != index_2_frame_ptr_prun.end() && "edge to vertex not added!");
- FrameBasePtr frame_new_ptr_full = index_2_frame_ptr_full[edge_new];
- FrameBasePtr frame_new_ptr_prun = index_2_frame_ptr_prun[edge_new];
- frame_new_ptr_full->addCapture(capture_ptr_full);
- frame_new_ptr_prun->addCapture(capture_ptr_prun);
- capture_ptr_full->addFeature(feature_ptr_full);
- capture_ptr_prun->addFeature(feature_ptr_prun);
- FactorOdom2DAnalytic* factor_ptr_full = new FactorOdom2DAnalytic(feature_ptr_full, frame_old_ptr_full);
- FactorOdom2DAnalytic* factor_ptr_prun = new FactorOdom2DAnalytic(feature_ptr_prun, frame_old_ptr_prun);
- feature_ptr_full->addFactor(factor_ptr_full);
- feature_ptr_prun->addFactor(factor_ptr_prun);
- //std::cout << "Added edge! " << factor_ptr_prun->id() << " from vertex " << factor_ptr_prun->getCapture()->getFrame()->id() << " to " << factor_ptr_prun->getFrameOther()->id() << std::endl;
- //std::cout << "vector " << factor_ptr_prun->getMeasurement().transpose() << std::endl;
- //std::cout << "information " << std::endl << edge_information << std::endl;
- //std::cout << "covariance " << std::endl << factor_ptr_prun->getMeasurementCovariance() << std::endl;
-
- t1 = clock();
- Scalar xi = *(frame_old_ptr_prun->getP()->get());
- Scalar yi = *(frame_old_ptr_prun->getP()->get()+1);
- Scalar thi = *(frame_old_ptr_prun->getO()->get());
- Scalar si = sin(thi);
- Scalar ci = cos(thi);
- Scalar xj = *(frame_new_ptr_prun->getP()->get());
- Scalar yj = *(frame_new_ptr_prun->getP()->get()+1);
- Eigen::MatrixXs Ji(3,3), Jj(3,3);
- Ji << -ci,-si,-(xj-xi)*si+(yj-yi)*ci,
- si,-ci,-(xj-xi)*ci-(yj-yi)*si,
- 0, 0, -1;
- Jj << ci, si, 0,
- -si, ci, 0,
- 0, 0, 1;
- //std::cout << "Ji" << std::endl << Ji << std::endl;
- //std::cout << "Jj" << std::endl << Jj << std::endl;
- Eigen::SparseMatrix<Scalar> DeltaLambda(Lambda.rows(), Lambda.cols());
- insertSparseBlock((Ji.transpose() * edge_information * Ji).sparseView(), DeltaLambda, edge_old*3, edge_old*3);
- insertSparseBlock((Jj.transpose() * edge_information * Jj).sparseView(), DeltaLambda, edge_new*3, edge_new*3);
- insertSparseBlock((Ji.transpose() * edge_information * Jj).sparseView(), DeltaLambda, edge_old*3, edge_new*3);
- insertSparseBlock((Jj.transpose() * edge_information * Ji).sparseView(), DeltaLambda, edge_new*3, edge_old*3);
- Lambda = Lambda + DeltaLambda;
- t_sigma_manual += ((double) clock() - t1) / CLOCKS_PER_SEC;
- }
- }
- else
- assert("unknown line");
- }
- printf("\nGraph loaded!\n");
- }
- else
- printf("\nError opening file\n");
-
- // PRIOR
- FrameBasePtr first_frame_full = wolf_problem_full->getTrajectory()->getFrameList().front();
- FrameBasePtr first_frame_prun = wolf_problem_prun->getTrajectory()->getFrameList().front();
- CaptureFix* initial_covariance_full = new CaptureFix(TimeStamp(0), new SensorBase("ABSOLUTE POSE", nullptr, nullptr, nullptr, 0), first_frame_full->getState(), Eigen::Matrix3s::Identity() * 0.01);
- CaptureFix* initial_covariance_prun = new CaptureFix(TimeStamp(0), new SensorBase("ABSOLUTE POSE", nullptr, nullptr, nullptr, 0), first_frame_prun->getState(), Eigen::Matrix3s::Identity() * 0.01);
- first_frame_full->addCapture(initial_covariance_full);
- first_frame_prun->addCapture(initial_covariance_prun);
- initial_covariance_full->process();
- initial_covariance_prun->process();
- //std::cout << "initial covariance: factor " << initial_covariance_prun->getFeatureList().front()->getFactorFromList().front()->id() << std::endl << initial_covariance_prun->getFeatureList().front()->getMeasurementCovariance() << std::endl;
- t1 = clock();
- Eigen::SparseMatrix<Scalar> DeltaLambda(Lambda.rows(), Lambda.cols());
- insertSparseBlock((Eigen::Matrix3s::Identity() * 100).sparseView(), DeltaLambda, 0, 0);
- Lambda = Lambda + DeltaLambda;
- t_sigma_manual += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // COMPUTE COVARIANCES
- FactorBasePtrList factors;
- wolf_problem_prun->getTrajectory()->getFactorList(factors);
- // Manual covariance computation
- t1 = clock();
- Eigen::SimplicialLLT<Eigen::SparseMatrix<Scalar>> chol(Lambda); // performs a Cholesky factorization of A
- Eigen::MatrixXs Sigma = chol.solve(Eigen::MatrixXs::Identity(Lambda.rows(), Lambda.cols()));
- t_sigma_manual += ((double) clock() - t1) / CLOCKS_PER_SEC;
- //std::cout << "Lambda" << std::endl << Lambda << std::endl;
- //std::cout << "Sigma" << std::endl << Sigma << std::endl;
-
- std::cout << " ceres is computing covariances..." << std::endl;
- t1 = clock();
- ceres_manager_prun->computeCovariances(ALL);//ALL_MARGINALS
- double t_sigma_ceres = ((double) clock() - t1) / CLOCKS_PER_SEC;
- std::cout << "computed!" << std::endl;
-
- t1 = clock();
-
- for (auto c_it=factors.begin(); c_it!=factors.end(); c_it++)
- {
- if ((*c_it)->getCategory() != FAC_FRAME) continue;
-
- // Measurement covariance
- Sigma_z = (*c_it)->getFeature()->getMeasurementCovariance();
- //std::cout << "Sigma_z" << std::endl << Sigma_z << std::endl;
- //std::cout << "Sigma_z.determinant() = " << Sigma_z.determinant() << std::endl;
-
- // NEW WAY
- // State covariance
- //11
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getFrameOther()->getP(), Sigma_11);
- //12
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getFrameOther()->getO(), Sigma_12);
- //13
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_13);
- //14
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_14);
-
- //22
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getFrameOther()->getO(), Sigma_22);
- //23
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_23);
- //24
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_24);
-
- //33
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getP(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_33);
- //34
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getP(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_34);
-
- //44
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getO(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_44);
-
-// std::cout << "Sigma_11" << std::endl << Sigma_11 << std::endl;
-// std::cout << "Sigma_12" << std::endl << Sigma_12 << std::endl;
-// std::cout << "Sigma_13" << std::endl << Sigma_13 << std::endl;
-// std::cout << "Sigma_14" << std::endl << Sigma_14 << std::endl;
-// std::cout << "Sigma_22" << std::endl << Sigma_22 << std::endl;
-// std::cout << "Sigma_23" << std::endl << Sigma_23 << std::endl;
-// std::cout << "Sigma_24" << std::endl << Sigma_24 << std::endl;
-// std::cout << "Sigma_33" << std::endl << Sigma_33 << std::endl;
-// std::cout << "Sigma_34" << std::endl << Sigma_34 << std::endl;
-// std::cout << "Sigma_44" << std::endl << Sigma_44 << std::endl;
-
- // jacobians
- ((FactorAnalytic*)(*c_it))->evaluatePureJacobians(jacobians);
- Eigen::MatrixXs& J1 = jacobians[0];
- Eigen::MatrixXs& J2 = jacobians[1];
- Eigen::MatrixXs& J3 = jacobians[2];
- Eigen::MatrixXs& J4 = jacobians[3];
-// std::cout << "J1" << std::endl << J1 << std::endl;
-// std::cout << "J2" << std::endl << J2 << std::endl;
-// std::cout << "J3" << std::endl << J3 << std::endl;
-// std::cout << "J4" << std::endl << J4 << std::endl;
-
- // Information gain
- Scalar IG_new = 0.5 * log( Sigma_z.determinant() /
- ( Sigma_z - (J1 * Sigma_11 * J1.transpose() +
- J1 * Sigma_12 * J2.transpose() +
- J1 * Sigma_13 * J3.transpose() +
- J1 * Sigma_14 * J4.transpose() +
- J2 * Sigma_12.transpose() * J1.transpose() +
- J2 * Sigma_22 * J2.transpose() +
- J2 * Sigma_23 * J3.transpose() +
- J2 * Sigma_24 * J4.transpose() +
- J3 * Sigma_13.transpose() * J1.transpose() +
- J3 * Sigma_23.transpose() * J2.transpose() +
- J3 * Sigma_33 * J3.transpose() +
- J3 * Sigma_34 * J4.transpose() +
- J4 * Sigma_14.transpose() * J1.transpose() +
- J4 * Sigma_24.transpose() * J2.transpose() +
- J4 * Sigma_34.transpose() * J3.transpose() +
- J4 * Sigma_44 * J4.transpose()) ).determinant() );
-
-// std::cout << "part = " << std::endl << (J1 * Sigma_11 * J1.transpose() +
-// J1 * Sigma_12 * J2.transpose() +
-// J1 * Sigma_13 * J3.transpose() +
-// J1 * Sigma_14 * J4.transpose() +
-// J2 * Sigma_12.transpose() * J1.transpose() +
-// J2 * Sigma_22 * J2.transpose() +
-// J2 * Sigma_23 * J3.transpose() +
-// J2 * Sigma_24 * J4.transpose() +
-// J3 * Sigma_13.transpose() * J1.transpose() +
-// J3 * Sigma_23.transpose() * J2.transpose() +
-// J3 * Sigma_33 * J3.transpose() +
-// J3 * Sigma_34 * J4.transpose() +
-// J4 * Sigma_14.transpose() * J1.transpose() +
-// J4 * Sigma_24.transpose() * J2.transpose() +
-// J4 * Sigma_34.transpose() * J3.transpose() +
-// J4 * Sigma_44 * J4.transpose()) << std::endl;
- std::cout << "IG_new = " << IG_new << std::endl;
-
- // OLD WAY
- // ii (old)
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getFrameOther()->getP(), Sigma_ii, 0, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getFrameOther()->getO(), Sigma_ii, 0, 2);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getFrameOther()->getP(), Sigma_ii, 2, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getFrameOther()->getO(), Sigma_ii, 2, 2);
-// std::cout << "Sigma_ii" << std::endl << Sigma_ii << std::endl;
-// std::cout << "Sigma(i,i)" << std::endl << Sigma.block<3,3>(frame_ptr_2_index_prun[(*c_it)->getFrameTo()]*3, frame_ptr_2_index_prun[(*c_it)->getFrameTo()]*3) << std::endl;
- // jj (new)
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getP(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_jj, 0, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getP(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_jj, 0, 2);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getO(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_jj, 2, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getCapture()->getFrame()->getO(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_jj, 2, 2);
-// std::cout << "Sigma_jj" << std::endl << Sigma_jj << std::endl;
-// std::cout << "Sigma(j,j)" << std::endl << Sigma.block<3,3>(frame_ptr_2_index_prun[(*c_it)->getCapture()->getFrame()]*3, frame_ptr_2_index_prun[(*c_it)->getCapture()->getFrame()]*3) << std::endl;
- // ij (old-new)
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_ij, 0, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getP(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_ij, 0, 2);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getCapture()->getFrame()->getP(), Sigma_ij, 2, 0);
- wolf_problem_prun->getCovarianceBlock((*c_it)->getFrameOther()->getO(), (*c_it)->getCapture()->getFrame()->getO(), Sigma_ij, 2, 2);
-// std::cout << "Sigma_ij" << std::endl << Sigma_ij << std::endl;
-// std::cout << "Sigma(i,j)" << std::endl << Sigma.block<3,3>(frame_ptr_2_index_prun[(*c_it)->getFrameTo()]*3, frame_ptr_2_index_prun[(*c_it)->getCapture()->getFrame()]*3) << std::endl;
-
- //jacobian
- xi = *(*c_it)->getFrameOther()->getP()->get();
- yi = *((*c_it)->getFrameOther()->getP()->get()+1);
- thi = *(*c_it)->getFrameOther()->getO()->get();
- si = sin(thi);
- ci = cos(thi);
- xj = *(*c_it)->getCapture()->getFrame()->getP()->get();
- yj = *((*c_it)->getCapture()->getFrame()->getP()->get()+1);
-
- Ji << -ci,-si,-(xj-xi)*si+(yj-yi)*ci,
- si,-ci,-(xj-xi)*ci-(yj-yi)*si,
- 0, 0, -1;
- Jj << ci, si, 0,
- -si, ci, 0,
- 0, 0, 1;
-// std::cout << "Ji" << std::endl << Ji << std::endl;
-// std::cout << "Jj" << std::endl << Jj << std::endl;
-
- //std::cout << "denominador : " << std::endl << Sigma_z - (Ji * Sigma_ii * Ji.transpose() + Jj * Sigma_jj * Jj.transpose() + Ji * Sigma_ij * Jj.transpose() + Jj * Sigma_ij.transpose() * Ji.transpose()) << std::endl;
- // Information gain
- Scalar IG = 0.5 * log( Sigma_z.determinant() / (Sigma_z - (Ji * Sigma_ii * Ji.transpose() + Jj * Sigma_jj * Jj.transpose() + Ji * Sigma_ij * Jj.transpose() + Jj * Sigma_ij.transpose() * Ji.transpose())).determinant() );
-
-// std::cout << "part = " << std::endl << (Ji * Sigma_ii * Ji.transpose() +
-// Jj * Sigma_jj * Jj.transpose() +
-// Ji * Sigma_ij * Jj.transpose() +
-// Jj * Sigma_ij.transpose() * Ji.transpose()) << std::endl;
- std::cout << "IG = " << IG << std::endl;
-
- std::cout << "difference IG = " << std::abs(IG - IG_new) << std::endl;
- assert((std::abs((IG - IG_new)/IG) < 0.1 || std::isnan(IG - IG_new)) && "not equals information gains");
-
- if (IG < 2 && IG > 0 && !std::isnan(IG))
- {
- // Store as a candidate to be prunned, ordered by information gain
- auto ordered_fac_it = ordered_fac_ptr.begin();
- for (auto ordered_ig_it = ordered_ig.begin(); ordered_ig_it != ordered_ig.end(); ordered_ig_it++, ordered_fac_it++ )
- if (IG < (*ordered_ig_it))
- {
- ordered_ig.insert(ordered_ig_it, IG);
- ordered_fac_ptr.insert(ordered_fac_it, (*c_it));
- break;
- }
- ordered_ig.insert(ordered_ig.end(), IG);
- ordered_fac_ptr.insert(ordered_fac_ptr.end(), (*c_it));
- }
- }
-
- // PRUNNING
- std::vector<bool> any_inactive_in_frame(wolf_problem_prun->getTrajectory()->getFrameList().size(), false);
- for (auto c_it = ordered_fac_ptr.begin(); c_it != ordered_fac_ptr.end(); c_it++ )
- {
- // Check heuristic: factor do not share node with any inactive factor
- unsigned int& index_frame = frame_ptr_2_index_prun[(*c_it)->getCapture()->getFrame()];
- unsigned int& index_frame_other = frame_ptr_2_index_prun[(*c_it)->getFrameOther()];
-
- if (!any_inactive_in_frame[index_frame] && !any_inactive_in_frame[index_frame_other])
- {
- std::cout << "setting inactive" << (*c_it)->id() << std::endl;
- (*c_it)->setStatus(FAC_INACTIVE);
- std::cout << "set!" << std::endl;
- any_inactive_in_frame[index_frame] = true;
- any_inactive_in_frame[index_frame_other] = true;
- }
- }
-
- double t_ig = ((double) clock() - t1) / CLOCKS_PER_SEC;
- std::cout << "manual sigma computation " << t_sigma_manual << "s" << std::endl;
- std::cout << "ceres sigma computation " << t_sigma_ceres << "s" << std::endl;
- std::cout << "information gain computation " << t_ig << "s" << std::endl;
-
- // SOLVING PROBLEMS
- std::cout << "FULL PROBLEM" << std::endl;
- std::cout << "solving..." << std::endl;
- summary_full = ceres_manager_full->solve();
- std::cout << summary_full.FullReport() << std::endl;
- std::cout << "PRUNNED PROBLEM" << std::endl;
- std::cout << "solving..." << std::endl;
- summary_prun = ceres_manager_prun->solve();
- std::cout << summary_prun.FullReport() << std::endl;
-
- delete wolf_problem_full; //not necessary to delete anything more, wolf will do it!
- std::cout << "wolf_problem_ deleted!" << std::endl;
- delete ceres_manager_full;
- delete ceres_manager_prun;
- std::cout << "ceres_manager deleted!" << std::endl;
- //End message
- std::cout << " =========================== END ===============================" << std::endl << std::endl;
-
- //exit
- return 0;
-}
diff --git a/demos/demo_wolf_root.cpp b/demos/demo_wolf_root.cpp
deleted file mode 100644
index ff78c97b0..000000000
--- a/demos/demo_wolf_root.cpp
+++ /dev/null
@@ -1,19 +0,0 @@
-/**
- * \file test_wolf_root.cpp
- *
- * Created on: Apr 12, 2016
- * \author: Jeremie Deray
- */
-
-//Wolf
-#include "base/common/wolf.h"
-
-//std
-#include <iostream>
-
-int main(int /*argc*/, char** /*argv*/)
-{
- std::cout << "Your wolf root directory is (_WOLF_ROOT_DIR) : " << _WOLF_ROOT_DIR << std::endl;
-
- return 1;
-}
diff --git a/demos/demo_wolf_tree.cpp b/demos/demo_wolf_tree.cpp
deleted file mode 100644
index 9a0075a93..000000000
--- a/demos/demo_wolf_tree.cpp
+++ /dev/null
@@ -1,59 +0,0 @@
-// Testing create and delete full wolf tree with odometry captures
-
-//std includes
-#include <iostream>
-#include <memory>
-#include <random>
-#include <cmath>
-#include <queue>
-
-//Wolf includes
-#include "wolf_manager.h"
-
-int main(int argc, char** argv)
-{
- using namespace wolf;
-
- //Welcome message
- std::cout << std::endl << " ========= WOLF TREE test ===========" << std::endl << std::endl;
-
- SensorOdom2D* odom_sensor_ptr_ = new SensorOdom2D(std::make_shared<StateBlock>(Eigen::Vector3s::Zero()),
- std::make_shared<StateBlock>(Eigen::Vector1s::Zero()), 0.1, 0.1);
- //std::cout << " odom sensor created!" << std::endl;
-
- WolfManager* wolf_manager_ = new WolfManager(FRM_PO_2D, //frame structure
- odom_sensor_ptr_, //odom sensor
- Eigen::Vector3s::Zero(), //prior
- Eigen::Matrix3s::Identity()*0.01, //prior cov
- 5, //window size
- 1); //time for new keyframe
- //std::cout << " wolf_manager_ created!" << std::endl;
-
- wolf_manager_->addSensor(odom_sensor_ptr_);
- //std::cout << " odom sensor added!" << std::endl;
-
- //main loop
- for (unsigned int ii = 0; ii<1000; ii++)
- {
- // Add sintetic odometry
- wolf_manager_->addCapture(new CaptureOdom2D(TimeStamp(ii*0.1),
- TimeStamp(ii*0.1+0.01),
- odom_sensor_ptr_,
- Eigen::Vector3s(0.1, 0. ,0.05)));
- //std::cout << " capture added!" << std::endl;
-
- // update wolf tree
- wolf_manager_->update();
- //std::cout << " updated!" << std::endl;
- }
- //std::cout << " end for!" << std::endl;
-
- delete wolf_manager_; //not necessary to delete anything more, wolf will do it!
-
- //End message
- std::cout << " =========================== END ===============================" << std::endl << std::endl;
-
- //exit
- return 0;
-}
-
diff --git a/demos/demo_yaml.cpp b/demos/demo_yaml.cpp
deleted file mode 100644
index 5181d73ac..000000000
--- a/demos/demo_yaml.cpp
+++ /dev/null
@@ -1,94 +0,0 @@
-/**
- * \file yaml-test.cpp
- *
- * Created on: May 1, 2016
- * \author: jsola
- */
-
-#include "base/math/pinhole_tools.h"
-#include "yaml/yaml_conversion.h"
-#include "processor_image_feature.h"
-#include "base/common/factory.h"
-
-#include <yaml-cpp/yaml.h>
-
-#include <eigen3/Eigen/Dense>
-
-#include <iostream>
-#include <fstream>
-
-int main()
-{
-
- //=============================================================================================
- std::string wolf_root = _WOLF_ROOT_DIR;
- std::cout << "\nwolf root directory: " << wolf_root << std::endl;
- //=============================================================================================
-
- using namespace Eigen;
- using namespace wolf;
- using std::string;
- using YAML::Node;
-
- // Camera parameters
-
- YAML::Node camera_config = YAML::LoadFile(wolf_root + "/src/examples/camera.yaml");
-
- if (camera_config["sensor type"])
- {
- std::string sensor_type = camera_config["sensor type"].as<std::string>();
-
- std::string sensor_name = camera_config["sensor name"].as<std::string>();
-
- YAML::Node params = camera_config["intrinsic"];
-
- // convert yaml to Eigen
- Vector3s pos = camera_config["extrinsic"]["position"].as<Vector3s>();
- Vector3s ori = camera_config["extrinsic"]["orientation"].as<Vector3s>() * M_PI / 180;
- Vector2s size = params["image size"].as<Vector2s>();
- Vector4s intrinsic = params["pinhole model"].as<Vector4s>();
- VectorXs distortion = params["distortion"].as<VectorXs>();
-
- // compute correction model
- VectorXs correction(distortion.size());
- pinhole::computeCorrectionModel(intrinsic, distortion, correction);
-
- // output
- std::cout << "sensor type : " << sensor_type << std::endl;
- std::cout << "sensor name : " << sensor_name << std::endl;
- std::cout << "sensor extrinsics : " << std::endl;
- std::cout << "\tposition : " << pos.transpose() << std::endl;
- std::cout << "\torientation : " << ori.transpose() << std::endl;
- std::cout << "sensor parameters : " << std::endl;
- std::cout << "\timage size : " << size.transpose() << std::endl;
- std::cout << "\tpinhole model : " << intrinsic.transpose() << std::endl;
- std::cout << "\tdistoriton : " << distortion.transpose() << std::endl;
- std::cout << "\tcorrection : " << correction.transpose() << std::endl;
- }
- else
- std::cout << "Bad configuration file. No sensor type found." << std::endl;
-
-// // Processor Image parameters
-//
-// ProcessorParamsImage p;
-//
-// Node params = YAML::LoadFile(wolf_root + "/src/examples/processor_image_feature.yaml");
-//
-// if (params["processor type"])
-// {
-// Node as = params["active search"];
-// p.active_search.grid_width = as["grid width"].as<unsigned int>();
-// p.active_search.grid_height = as["grid height"].as<unsigned int>();
-// p.active_search.separation = as["separation"].as<unsigned int>();
-//
-// Node img = params["image"];
-// p.image.width = img["width"].as<unsigned int>();
-// p.image.height = img["height"].as<unsigned int>();
-//
-// Node alg = params["algorithm"];
-// p.max_new_features = alg["maximum new features"].as<unsigned int>();
-// p.min_features_for_keyframe = alg["minimum features for new keyframe"].as<unsigned int>();
-// }
-
- return 0;
-}
diff --git a/demos/demo_yaml_conversions.cpp b/demos/demo_yaml_conversions.cpp
deleted file mode 100644
index b8e1f41f9..000000000
--- a/demos/demo_yaml_conversions.cpp
+++ /dev/null
@@ -1,54 +0,0 @@
-/**
- * \file test_yaml_conversions.cpp
- *
- * Created on: May 15, 2016
- * \author: jsola
- */
-
-#include "core/yaml/yaml_conversion.h"
-
-#include <yaml-cpp/yaml.h>
-
-#include <eigen3/Eigen/Dense>
-
-#include <iostream>
-//#include <fstream>
-
-int main()
-{
-
- using namespace Eigen;
-
- std::cout << "\nTrying different yaml specs for matrix..." << std::endl;
-
- YAML::Node mat_sized_23, mat_sized_33, mat_sized_bad, mat_23, mat_33, mat_bad;
-
- mat_sized_23 = YAML::Load("[[2, 3] ,[1, 2, 3, 4, 5, 6] ]"); // insensitive to spacing
- mat_sized_33 = YAML::Load("[[3, 3] ,[1, 2, 3, 4, 5, 6, 7, 8, 9]]"); // insensitive to spacing
-
- mat_23 = YAML::Load("[1, 2, 3, 4, 5, 6]"); // insensitive to spacing
- mat_33 = YAML::Load("[1, 2, 3, 4, 5, 6, 7, 8, 9]"); // insensitive to spacing
-
- MatrixXd Mx = mat_sized_23.as<MatrixXd>();
- std::cout << "Dyn-Dyn [[2,3] ,[1, 2, 3, 4, 5, 6] ] = \n" << Mx << std::endl;
-
- Matrix<double, 2, Dynamic> M2D = mat_sized_23.as<Matrix<double, 2, Dynamic>>();
- std::cout << "2-Dyn [[2,3] ,[1, 2, 3, 4, 5, 6] ] = \n" << M2D << std::endl;
-
- Matrix<double, Dynamic, 3> MD3 = mat_sized_23.as<Matrix<double, Dynamic, 3>>();
- std::cout << "Dyn-3 [[2,3] ,[1, 2, 3, 4, 5, 6] ] = \n" << MD3 << std::endl;
-
- Matrix3d M3 = mat_sized_33.as<Matrix3d>();
- std::cout << "3-3 [[3,3] ,[1, 2, 3, 4, 5, 6, 7, 8, 9] ] = \n" << M3 << std::endl;
-
- M2D = mat_23.as<Matrix<double, 2, Dynamic>>();
- std::cout << "2-Dyn [1, 2, 3, 4, 5, 6] = \n" << M2D << std::endl;
-
- MD3 = mat_23.as<Matrix<double, Dynamic, 3>>();
- std::cout << "Dyn-3 [1, 2, 3, 4, 5, 6] = \n" << MD3 << std::endl;
-
- M3 = mat_33.as<Matrix3d>();
- std::cout << "3-3 [1, 2, 3, 4, 5, 6, 7, 8, 9] = \n" << M3 << std::endl;
-
- return 0;
-}
diff --git a/demos/input_M3500b_toro.graph b/demos/input_M3500b_toro.graph
deleted file mode 100644
index 21d4f4104..000000000
--- a/demos/input_M3500b_toro.graph
+++ /dev/null
@@ -1,8953 +0,0 @@
-VERTEX2 0 0.000000 0.000000 0.000000
-VERTEX2 1 1.030390 0.011350 0.387567
-VERTEX2 2 1.991252 0.340250 0.471361
-VERTEX2 3 2.910224 0.800262 0.167817
-VERTEX2 4 2.730618 1.788506 1.475181
-VERTEX2 5 2.813120 2.801285 1.677202
-VERTEX2 6 2.697609 3.818661 1.740977
-VERTEX2 7 2.532293 4.762025 1.885102
-VERTEX2 8 2.861812 3.792586 -1.443491
-VERTEX2 9 3.005620 2.779204 -1.588453
-VERTEX2 10 3.010151 1.775618 -1.498040
-VERTEX2 11 3.100182 0.802342 -1.878003
-VERTEX2 12 3.377318 1.760265 1.280066
-VERTEX2 13 3.643665 2.714611 1.353133
-VERTEX2 14 3.839241 3.640087 1.153732
-VERTEX2 15 4.238446 4.556982 1.114735
-VERTEX2 16 5.176343 4.139078 -0.188893
-VERTEX2 17 6.146369 3.973886 0.126050
-VERTEX2 18 7.092254 4.123574 -0.094755
-VERTEX2 19 8.081760 4.048820 -0.025535
-VERTEX2 20 8.009905 3.034004 -1.535535
-VERTEX2 21 8.039875 2.035990 -1.789560
-VERTEX2 22 7.834117 1.068866 -1.615560
-VERTEX2 23 7.796816 0.080123 -1.744510
-VERTEX2 24 7.963836 1.068135 1.518927
-VERTEX2 25 8.011572 2.082374 1.270385
-VERTEX2 26 8.318896 3.068591 1.288482
-VERTEX2 27 8.602681 4.016183 1.405397
-VERTEX2 28 7.626395 4.130080 3.066433
-VERTEX2 29 6.600082 4.228693 2.906166
-VERTEX2 30 5.612239 4.448738 2.978911
-VERTEX2 31 4.632725 4.601591 2.860578
-VERTEX2 32 4.894579 5.539797 1.067367
-VERTEX2 33 5.388198 6.458157 1.152328
-VERTEX2 34 5.775578 7.370271 1.257071
-VERTEX2 35 6.054859 8.326758 1.326843
-VERTEX2 36 5.085698 8.556889 2.727556
-VERTEX2 37 4.161165 8.951055 2.843635
-VERTEX2 38 3.164181 9.241874 2.841768
-VERTEX2 39 2.200830 9.532630 2.819498
-VERTEX2 40 1.835753 8.616074 -1.942024
-VERTEX2 41 1.448809 7.710071 -1.982670
-VERTEX2 42 1.075490 6.778997 -1.751631
-VERTEX2 43 0.885198 5.811020 -1.883499
-VERTEX2 44 0.595605 4.876047 -2.046603
-VERTEX2 45 0.103124 4.009236 -2.027326
-VERTEX2 46 -0.340778 3.110313 -1.936592
-VERTEX2 47 -0.729765 2.188845 -1.953972
-VERTEX2 48 -0.363779 3.065323 1.478864
-VERTEX2 49 -0.282708 4.079553 1.652104
-VERTEX2 50 -0.392495 5.089453 1.868665
-VERTEX2 51 -0.715409 6.091060 2.097129
-VERTEX2 52 0.141156 6.576218 0.485381
-VERTEX2 53 1.048636 7.065015 -0.076897
-VERTEX2 54 2.029903 6.999232 0.143914
-VERTEX2 55 3.033679 7.129204 0.047546
-VERTEX2 56 3.076840 6.145157 -1.134105
-VERTEX2 57 3.498102 5.204006 -1.093796
-VERTEX2 58 3.939516 4.325175 -1.332336
-VERTEX2 59 4.189390 3.346256 -1.590844
-VERTEX2 60 3.180599 3.346370 3.035322
-VERTEX2 61 2.194086 3.455690 3.015793
-VERTEX2 62 1.222517 3.591341 -3.140766
-VERTEX2 63 0.214837 3.627602 2.949331
-VERTEX2 64 0.419924 4.605033 1.683679
-VERTEX2 65 0.319731 5.638263 1.852402
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-EDGE2 1762 1763 0.994133 0.000537 0.223428 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1769 1770 1.021690 -0.015925 0.390671 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1771 1772 -0.971108 -0.032772 3.120642 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1773 1774 1.000360 0.008063 0.302080 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1774 1775 1.030470 -0.005846 -0.151598 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1775 1776 0.056940 -0.999835 -1.219564 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1776 1777 0.952765 -0.064164 0.115330 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1777 1778 1.022310 0.005763 -0.259410 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1778 1779 1.020890 0.011783 -0.353095 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1779 1780 0.004131 0.963550 1.412370 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1780 1781 0.957538 -0.005472 -0.150239 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1781 1782 0.961750 0.019297 0.424625 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1782 1783 0.971965 0.021710 -0.263578 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1783 1784 0.026461 -1.009080 -0.994624 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1784 1785 0.961514 0.026669 -0.528010 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1785 1786 0.969123 -0.022763 -0.026634 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1786 1787 1.054740 -0.001293 -0.097128 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1787 1788 0.002906 1.000750 1.619913 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1788 1789 0.989949 0.030519 0.144018 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1789 1790 0.978811 -0.016695 -0.159302 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1790 1791 0.999211 -0.024870 0.060227 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1791 1792 -0.991450 0.013199 2.818539 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1792 1793 1.013680 -0.009616 -0.178233 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1793 1794 1.020690 -0.007120 0.321529 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1794 1795 0.988451 -0.041932 0.202625 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1795 1796 -0.992272 -0.003356 2.916928 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1796 1797 1.015210 -0.025659 0.277512 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1797 1798 0.993933 0.005799 -0.043338 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1798 1799 0.983679 -0.004110 0.058639 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1799 1800 -0.024830 0.975395 1.663751 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1800 1801 1.017240 -0.026203 0.065387 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1801 1802 0.989772 0.002603 0.444020 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1802 1803 0.979138 0.007411 0.050342 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1803 1804 0.039484 0.994646 1.597748 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1804 1805 1.020490 0.007235 -0.055955 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1805 1806 1.013020 0.016633 -0.272228 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1806 1807 0.981497 0.008408 0.043311 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1807 1808 0.003716 -0.986025 -1.480528 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1808 1809 1.022180 0.018680 0.109474 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1809 1810 1.000740 -0.002997 0.147047 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1810 1811 0.996342 -0.013393 0.204769 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1812 1813 1.019160 0.023153 0.104917 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1813 1814 0.969921 0.000494 0.164373 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1814 1815 1.042410 -0.005742 -0.092361 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1824 1825 0.988441 0.022422 0.036865 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1825 1826 1.002530 0.002413 -0.183570 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1826 1827 1.017720 -0.018900 0.051315 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1827 1828 -0.989965 -0.004048 2.849065 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1828 1829 1.008210 0.008764 0.161586 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1829 1830 1.014000 0.027351 -0.141784 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1830 1831 1.000500 -0.019047 0.087905 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1833 1834 0.977782 0.017499 0.221470 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1839 1840 -0.031984 0.949347 1.772166 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1847 1848 -0.012302 -0.959548 -1.459573 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1848 1849 0.982197 -0.006409 -0.270950 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1849 1850 1.005470 0.012332 0.028406 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1850 1851 0.983517 0.007817 0.169403 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1860 1861 1.041070 0.032575 -0.303862 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1861 1862 0.995103 -0.003864 0.178733 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1862 1863 1.023810 0.031081 0.087780 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1863 1864 -0.031269 0.991941 1.488608 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1864 1865 1.010430 -0.022713 -0.064752 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1865 1866 0.961861 -0.023818 0.033868 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1866 1867 0.995316 -0.034185 -0.142311 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1878 1879 0.940250 -0.037432 -0.088998 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1879 1880 -0.021389 0.988447 1.433996 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1880 1881 1.018190 -0.004343 0.123017 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1881 1882 0.974757 -0.044462 -0.246935 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1884 1885 1.013850 0.016637 0.257996 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1886 1887 1.007150 0.016675 -0.350608 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1887 1888 0.009653 0.990512 1.469179 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1888 1889 1.048430 -0.008036 0.453577 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1889 1890 0.972008 -0.063256 0.163750 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1890 1891 1.040260 -0.016407 -0.141646 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1891 1892 0.018421 -1.001720 -1.684593 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1892 1893 1.011270 0.022831 -0.048041 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1893 1894 1.004990 -0.012281 -0.029733 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1894 1895 0.998691 -0.049117 -0.209315 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1895 1896 -0.013282 -0.997564 -1.151662 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1896 1897 0.946457 -0.029009 0.219354 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1897 1898 0.994255 0.030064 0.080733 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1898 1899 1.031700 -0.026189 0.259800 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1899 1900 -1.051200 -0.018969 2.971452 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1900 1901 0.968351 0.025239 -0.014441 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1901 1902 1.015020 -0.005390 0.039336 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1902 1903 1.027150 -0.025621 -0.230619 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1903 1904 0.013783 -1.001070 -1.415427 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1904 1905 0.991977 0.002636 -0.055267 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1905 1906 0.970135 -0.014302 0.259618 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1906 1907 1.011100 -0.005782 0.141624 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1907 1908 0.023789 1.065030 1.447238 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1908 1909 0.985849 -0.018981 0.266899 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1909 1910 1.040330 0.039629 0.214176 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1910 1911 0.969525 -0.006903 0.180018 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1911 1912 -0.030946 1.001070 1.756791 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1912 1913 1.006680 -0.003869 -0.086623 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1913 1914 1.012320 -0.008238 -0.324093 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1914 1915 0.981227 0.003851 0.122193 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1915 1916 -0.015771 1.008660 1.767357 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1916 1917 0.995758 -0.005949 0.224644 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1917 1918 1.009090 -0.034097 -0.209034 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1918 1919 0.997316 -0.040255 -0.137525 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1919 1920 0.021714 -1.043370 -1.416988 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1920 1921 1.016470 -0.009130 0.159578 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1921 1922 0.997911 0.029678 0.177186 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1922 1923 0.967911 0.034560 -0.209232 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1923 1924 -0.004873 0.991019 1.691093 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1924 1925 1.017470 0.010660 0.070271 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1925 1926 0.984683 -0.059702 0.182600 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1926 1927 0.964688 0.016487 -0.478114 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1927 1928 -0.023318 -1.003450 -1.764566 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1928 1929 1.026350 -0.033868 0.323388 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1929 1930 1.050260 0.010754 0.196731 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1930 1931 0.961452 0.037439 -0.341709 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1931 1932 0.019849 -0.997366 -1.748855 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1932 1933 1.019590 0.039934 -0.448505 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1933 1934 1.028170 -0.005051 0.007886 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1934 1935 1.008830 0.067951 0.016105 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1935 1936 -0.995970 -0.019982 3.020127 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1936 1937 0.987172 0.032078 -0.160384 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1937 1938 1.038230 0.014006 -0.184382 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1938 1939 0.988626 -0.032983 -0.357966 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1939 1940 1.016620 -0.029160 -0.269567 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1940 1941 0.982077 0.007146 0.108752 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1941 1942 1.001440 0.015425 0.017764 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1942 1943 0.983561 0.018599 0.212219 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1943 1944 0.985794 0.027860 0.133082 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1944 1945 1.018290 0.006961 0.008520 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1945 1946 0.982856 -0.009942 -0.070781 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1946 1947 1.000690 0.004596 -0.313003 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1947 1948 -0.003779 1.050160 1.464678 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1948 1949 0.988862 -0.003627 -0.025085 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1949 1950 1.006900 -0.016227 -0.065576 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1950 1951 1.007820 -0.010573 -0.345004 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1951 1952 0.025756 -0.987220 -1.742651 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1952 1953 0.949943 -0.004763 -0.188084 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1953 1954 0.998962 -0.028612 0.091328 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1954 1955 1.050640 -0.056139 0.007080 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1955 1956 0.038517 0.963756 1.486229 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1956 1957 0.938361 0.026511 -0.212802 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1957 1958 0.997767 0.047833 -0.205033 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1958 1959 0.995216 -0.017076 -0.410634 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1959 1960 0.016038 1.002660 1.873558 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1960 1961 1.051010 0.031449 -0.221647 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1961 1962 1.003100 -0.020270 -0.491363 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1962 1963 0.978209 -0.031376 -0.079308 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1963 1964 -1.003280 0.019054 -2.972433 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1964 1965 0.978539 0.020003 -0.194897 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1965 1966 1.020270 0.033554 -0.043582 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1966 1967 0.990613 -0.005521 0.013500 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1967 1968 -0.014273 -0.964791 -1.579587 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1968 1969 1.005750 -0.016200 0.228404 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1969 1970 1.011880 -0.001514 -0.291818 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1970 1971 0.996474 -0.039021 0.244738 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1971 1972 -0.965259 0.022969 -2.886616 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1972 1973 1.021340 -0.025372 0.078464 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1973 1974 0.989554 -0.024904 -0.182213 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1974 1975 0.997283 0.008209 -0.240998 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1975 1976 0.015782 0.997843 1.441208 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1976 1977 0.996526 0.027942 -0.130582 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1977 1978 1.022830 -0.015197 0.055674 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1978 1979 1.009760 0.025564 0.191706 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1979 1980 -0.006370 -1.024710 -1.347349 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1980 1981 0.981545 0.002806 0.177040 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1981 1982 1.007710 -0.015773 -0.037363 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1982 1983 1.002870 -0.015626 -0.011278 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1983 1984 0.009221 -1.011090 -1.539657 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1984 1985 1.008430 -0.020619 0.122177 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1985 1986 1.018970 -0.014423 -0.170223 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1986 1987 1.011310 -0.021775 0.116236 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1987 1988 1.025120 0.001791 -0.035105 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1988 1989 0.981354 0.016810 -0.375405 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1989 1990 1.016950 -0.014146 -0.147682 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1990 1991 0.971500 -0.024429 0.033105 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1991 1992 -1.020570 0.034192 -3.081870 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1992 1993 0.983384 -0.025637 0.109391 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1993 1994 0.987247 -0.010559 0.082855 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1994 1995 1.004440 0.028290 0.143755 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1995 1996 -0.035746 1.010730 1.646334 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1996 1997 1.010580 0.003843 -0.106504 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1997 1998 0.974704 0.013275 0.184402 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1998 1999 1.030440 0.010950 -0.000187 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1999 2000 0.992546 -0.008772 -0.043576 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2000 2001 0.940349 -0.006631 -0.178748 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2001 2002 1.068410 0.007070 0.164397 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2002 2003 1.042480 -0.007161 -0.161657 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2003 2004 -1.008860 -0.034767 -2.969573 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2004 2005 1.002220 -0.017538 -0.275872 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2005 2006 1.006190 -0.012172 0.005630 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2006 2007 1.014580 0.022707 -0.122760 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2007 2008 -1.015040 -0.016273 3.105569 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2008 2009 1.023270 0.001952 -0.260318 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2009 2010 0.980896 0.040167 -0.117082 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2010 2011 1.015000 -0.023482 0.193494 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2011 2012 -0.981526 -0.020971 -2.664883 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2012 2013 0.979661 0.025197 0.176540 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2013 2014 1.008670 -0.000253 -0.354353 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2014 2015 0.955407 0.043069 -0.118395 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2015 2016 -0.010939 -1.035910 -1.436789 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2016 2017 1.019780 0.013410 -0.121030 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2017 2018 1.012700 0.014139 0.423967 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2018 2019 1.015350 0.038756 -0.029182 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2019 2020 0.029734 -0.943963 -1.322295 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2020 2021 0.993207 0.006947 0.054954 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2021 2022 0.984309 -0.025611 0.015831 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2022 2023 1.041560 0.022534 0.350675 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2023 2024 0.006455 1.005940 1.347547 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2024 2025 0.976628 0.010311 -0.085320 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2025 2026 1.020090 -0.027414 -0.286652 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2026 2027 0.976556 0.041592 0.028133 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2027 2028 -0.983270 -0.013815 -3.076417 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2028 2029 0.991677 -0.010706 0.100632 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2029 2030 1.027050 -0.001327 0.192031 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2030 2031 1.021830 -0.058484 -0.258846 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2031 2032 0.012301 -0.995639 -1.308850 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2032 2033 1.022900 -0.000438 -0.397893 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2033 2034 0.989433 0.008658 0.072936 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2034 2035 0.995488 0.048026 -0.392394 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2035 2036 0.019810 1.008250 1.720162 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2036 2037 1.029170 -0.021064 0.046035 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2037 2038 0.999018 -0.020791 0.185146 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2038 2039 0.981758 -0.006766 0.161242 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2039 2040 -1.015480 0.026702 -2.847483 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2040 2041 0.980184 0.023174 -0.123329 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2041 2042 0.971523 0.009725 -0.281142 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2042 2043 1.007400 -0.026936 -0.442115 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2043 2044 0.003289 -1.012940 -1.148452 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2044 2045 1.035850 0.039481 0.239723 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2045 2046 0.933262 -0.034209 0.136000 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2046 2047 0.998488 0.001196 0.092565 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2047 2048 -1.009510 0.010345 2.989684 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2048 2049 1.014390 0.016811 0.000862 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2049 2050 1.005950 0.010759 -0.057518 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2050 2051 0.957288 -0.005589 0.084063 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2051 2052 -0.006942 -0.985960 -1.714910 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2052 2053 1.016960 0.007085 0.486383 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2053 2054 0.964718 -0.066712 -0.222829 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2054 2055 0.984921 -0.051171 0.154197 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2055 2056 -0.995745 -0.006755 -2.955629 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2056 2057 0.970021 -0.000399 -0.067565 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 1819 1835 -0.010830 -0.004956 -0.012113 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1264 1846 -0.980093 -1.029550 1.154472 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1271 1846 0.006543 0.984734 -1.522313 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1296 1847 -0.980522 0.047472 -1.734997 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1265 1849 0.007324 0.030923 -0.169971 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 667 1851 0.017787 0.033783 -1.520658 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 666 1851 1.000860 -0.006682 -1.613819 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1267 1851 0.014751 -0.031739 -0.133310 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1259 1852 0.987388 0.032652 -0.216412 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1856 1861 1.001410 0.018451 -3.101241 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1857 1861 0.007755 0.019954 2.953910 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1855 1864 -0.980483 -0.000596 3.005600 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1859 1864 -4.047550 -0.989426 -1.458430 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1853 1864 1.009570 -0.050749 -2.939799 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1854 1864 0.017373 -0.000680 3.048692 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 1856 1864 -0.982531 -0.985014 -1.566778 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1852 1865 0.998403 0.000784 3.092807 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1853 1866 -1.012020 -0.054794 3.121047 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1851 1868 1.010120 -0.041438 -0.208496 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1259 1869 0.025435 -2.001580 -1.754617 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 659 1873 2.006550 0.051249 3.050871 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 634 1874 0.976091 -0.987714 1.881122 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 683 1875 -0.003206 0.009378 -1.719856 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 637 1877 -0.015217 -0.005695 -0.091387 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 633 1877 0.004996 0.008405 -2.876661 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 608 1878 -0.991811 -1.001350 1.400317 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 615 1879 0.023068 0.034923 -1.439725 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 648 1886 -1.014960 -1.045130 1.404233 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 615 1888 -0.043234 -0.979152 -1.584862 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 563 1891 -0.018918 0.002471 1.621303 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 562 1891 0.976611 -0.000758 1.659359 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 603 1892 -1.005620 0.007646 3.119605 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 567 1894 -1.029700 -0.026622 -0.124872 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 599 1895 -0.009313 0.022371 1.479171 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 581 1896 0.995625 -0.045115 -2.929635 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 580 1897 1.037560 0.042838 -2.793288 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 581 1897 0.011062 0.012406 -3.120889 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 580 1898 0.007767 -0.000761 -2.904538 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 693 1899 -2.027630 0.019342 -1.778129 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 567 1904 1.006840 0.027757 0.045595 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 582 1904 0.992929 -1.006630 -1.328929 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 714 1907 0.983808 -0.015309 -1.550754 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 716 1907 -1.015100 -0.004468 1.564110 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 714 1908 2.021470 -0.021243 -0.246146 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 415 1909 2.037950 -0.014452 -2.752443 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 414 1911 1.009303 0.021084 -3.123446 134.164079 0.000000 134.164079 23.151158 0.000000 0.000000
-EDGE2 1909 1913 2.001330 2.000770 1.697945 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 595 1914 0.986292 0.004597 -2.777341 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 594 1914 2.011210 0.039655 3.105619 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 594 1915 0.956900 -0.009452 3.044766 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 595 1916 0.027690 -0.969365 -1.595956 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 596 1916 -0.026175 -0.039141 -0.341886 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 597 1917 -0.013807 0.001487 -0.213473 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 598 1917 -1.013653 0.012266 0.047593 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 600 1919 -0.981792 0.016899 1.544339 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 598 1919 0.988610 0.028227 0.318119 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 563 1923 -0.021495 -0.018837 -2.995303 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 572 1924 -0.030230 0.020506 0.025444 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1889 1926 -1.001200 0.022634 -3.028805 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 607 1926 -0.994124 -0.052017 0.063675 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 638 1927 0.973856 0.037990 -3.089009 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1887 1927 0.007841 0.015599 -1.574018 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 639 1927 -0.004398 0.009334 2.942292 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 647 1928 0.986739 0.013357 0.143867 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1886 1928 0.003117 -0.016517 -3.063957 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1881 1928 -0.956658 -0.001364 -0.234112 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1884 1929 0.976082 -0.019474 3.026240 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1881 1929 0.027876 -0.006818 -0.066393 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1884 1931 -0.997972 -0.004057 2.942486 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 519 1935 -0.020380 0.008875 1.624585 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 550 1935 1.060820 0.030482 1.585342 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 559 1936 1.005770 -0.029426 -0.215056 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1933 1937 0.037638 -0.000073 -2.796192 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1932 1937 1.001354 0.007475 2.750356 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 1932 1938 -0.020102 -0.022084 3.026463 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 1883 1938 -0.001480 -0.999908 1.727107 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1883 1939 0.050230 0.005542 1.924135 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1871 1941 1.974070 0.002981 2.944819 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1872 1942 -1.009578 1.014417 -1.687703 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 1871 1942 1.031780 -0.002135 -2.773280 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1868 1946 -0.035733 -0.018844 -3.061054 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 675 1947 0.048119 0.008014 1.381821 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1267 1947 0.046182 -0.020423 -3.083454 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1259 1948 -1.021840 -0.011865 2.832670 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 674 1948 -0.002307 0.008866 2.848049 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1867 1948 0.960130 -0.004011 0.096441 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 662 1949 1.040570 -1.989190 1.171999 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 664 1950 -0.017560 0.000987 3.082596 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 673 1950 -1.007390 -0.008573 -2.871133 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 680 1951 -1.015550 -0.012440 -1.756751 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 671 1952 -0.040135 -1.067720 -1.111398 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1754 1953 1.023490 1.960920 -1.336933 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1227 1953 2.038220 -0.006269 2.828178 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 679 1953 -0.044334 -2.003110 -1.378113 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1828 1955 -1.008380 0.026738 -0.331549 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1838 1959 0.960079 0.022115 -1.798646 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 789 1961 -0.028623 0.026898 -2.784547 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 790 1966 -0.040145 0.007678 0.196528 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 789 1966 1.010740 0.048194 0.351460 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1839 1967 -0.003271 -0.018728 -2.882932 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1827 1971 -0.037287 0.048466 1.630545 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1756 1971 -1.000480 0.001534 -1.267820 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1955 1971 0.020325 0.005030 -1.954811 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1226 1971 0.940694 0.002506 1.650511 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1228 1972 -0.011532 -0.032134 -0.094865 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1841 1973 -0.027176 0.000495 -3.116181 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 793 1973 0.010023 -0.024635 -2.914319 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1838 1975 0.993292 0.007587 -1.207692 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1232 1976 -0.051791 -0.021885 -0.097744 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 771 1978 -0.019719 1.014230 -1.764843 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 771 1979 -0.000206 0.003485 -1.602629 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 770 1980 0.058967 0.020185 -3.006845 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1242 1980 1.013800 0.969365 1.525785 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 767 1983 0.006000 0.036361 -3.104451 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 766 1984 1.024110 0.980924 1.736314 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1835 1991 3.956960 -0.096783 -1.687319 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1988 1993 0.993837 0.011343 -2.963335 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1988 1994 0.035207 0.015742 -3.016082 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1989 1994 -0.970148 -0.027328 3.069607 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1990 1994 -1.996790 -0.020248 -2.839786 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1987 1994 1.001550 0.000319 2.778374 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1988 1996 -0.971028 -0.973356 -1.280513 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1987 1996 -0.052882 -1.019580 -1.560994 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1230 2000 0.021388 0.014343 2.891810 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 1755 2002 0.992975 0.000187 -3.069583 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1955 2003 0.004573 -0.006991 -1.815159 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1968 2005 1.010680 -0.026294 -2.673915 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1230 2005 -0.991952 0.017318 0.144125 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2000 2006 -0.020501 0.003673 2.740731 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1840 2006 0.020880 0.017827 3.051711 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 790 2007 1.021550 -0.033538 1.550217 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 794 2010 -0.017384 0.031931 -0.078010 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1970 2010 0.001508 -0.005808 0.088076 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 1968 2014 -0.008449 0.004160 2.770941 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 792 2014 -0.019009 -0.027456 -2.948268 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1837 2016 1.001800 -0.001429 2.844492 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1820 2020 -0.009990 -0.012339 -0.216556 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1224 2022 -0.980207 -1.027030 1.428351 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 799 2022 -0.016362 1.025830 -1.046064 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1831 2023 -0.035729 0.006079 -1.677085 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1759 2023 0.032661 0.003237 -1.309894 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1739 2026 -0.030014 -1.007380 1.369317 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1715 2028 -0.019867 1.040800 1.554116 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1714 2028 0.977572 0.963022 1.833422 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1812 2028 -0.007393 0.000826 -0.103647 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1823 2030 0.026544 1.000880 -1.425695 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2023 2030 0.015186 1.021570 -1.432177 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1759 2030 0.988558 -0.010733 -3.005177 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1832 2030 -0.982808 -0.995503 1.366884 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1831 2031 0.029073 -0.031806 3.075670 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1820 2035 -1.000310 -0.018609 -2.995164 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2016 2038 0.020347 0.010353 3.045652 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2007 2039 -0.010566 0.004154 1.479201 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1974 2039 1.022580 0.010607 1.998684 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 792 2039 -0.975663 0.006343 -1.406875 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1958 2039 1.056480 0.025081 1.644088 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1837 2040 0.998594 -0.004310 2.922515 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1838 2041 -1.021900 -0.018406 -3.034380 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1837 2041 -0.035368 -0.037845 2.816644 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1836 2043 -1.005910 0.010857 -2.993642 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1836 2044 -1.013990 0.961023 1.694505 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2034 2044 -0.012104 -0.011055 -3.104571 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1818 2045 -0.984814 0.026111 -2.845615 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2022 2047 0.992697 0.005019 -0.169536 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 2024 2047 -0.999838 -0.008773 -1.209316 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 1815 2048 -0.015699 -0.993257 -1.574370 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
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-EDGE2 3369 3373 0.003175 0.029224 -2.956340 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3368 3374 0.013354 -0.004092 2.830090 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3369 3375 -2.018380 0.024854 2.963117 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3365 3375 1.977720 0.006191 -1.476287 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3355 3376 -3.951720 0.975272 1.679976 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3350 3377 -0.996170 -0.033531 3.108421 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3349 3377 0.004836 0.013466 2.993560 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3345 3378 2.001810 0.975390 -1.870317 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 3346 3378 1.039450 1.011150 -0.846462 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3347 3379 -0.011195 -0.010712 -1.731256 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3348 3379 -1.017020 -0.007679 3.134798 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3348 3380 -1.018335 -1.013008 -1.722364 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 3347 3380 1.024860 0.001338 0.050522 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3347 3381 2.008740 0.005463 -0.037821 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3378 3382 0.978103 3.012880 1.283611 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3371 3383 -0.025519 -4.014915 -0.330941 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 3387 3391 0.031890 3.981140 1.429867 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3388 3392 3.022650 1.026030 1.896932 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3392 3396 2.023940 0.007535 3.014493 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3393 3397 0.001861 0.030085 -3.019711 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3392 3398 0.008989 -0.002512 -3.008608 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3388 3399 2.982340 -0.013834 -1.323184 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3390 3399 1.011153 -0.005544 -1.402955 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 3391 3399 0.026188 0.001226 -1.432971 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3391 3400 1.016930 0.032600 0.115186 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3414 3423 1.011640 -0.006550 1.620970 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3425 3430 -0.990564 0.006053 -2.666628 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3418 3434 0.033170 0.015964 0.119233 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3420 3434 -0.000364 -0.006055 3.099049 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3414 3437 0.952499 -1.991030 1.486112 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3415 3438 -0.014616 -0.980767 1.880422 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3423 3438 -1.027110 -0.019608 0.163837 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3431 3438 -0.002667 0.955677 -1.681410 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3415 3439 -0.023824 0.006743 1.538493 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3429 3441 0.009141 0.024752 2.966199 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 3426 3442 -0.004190 0.032259 -0.086940 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3429 3442 -0.988224 -0.036270 -3.117034 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3429 3445 0.030241 0.015364 -0.171756 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3425 3445 -0.014296 -0.008301 3.060119 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3440 3446 0.020401 -0.009372 2.950129 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3439 3454 1.000290 0.012275 -3.056232 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3448 3454 0.014237 0.019249 3.108066 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3432 3455 -0.978312 0.032874 -0.303342 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3439 3455 0.023475 -0.002436 -3.028625 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3423 3456 1.006900 0.008129 0.153734 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3448 3457 1.014220 0.019537 -0.309286 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3464 3470 -0.006609 0.018518 2.944143 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 3463 3471 -0.008586 0.024989 1.429319 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 3464 3471 -1.033940 -0.023548 2.573105 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3462 3471 1.006910 -0.008297 1.638130 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3464 3472 0.021041 -0.005002 0.147376 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3443 3476 -1.024310 -0.018902 -2.870127 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3444 3476 0.013877 -0.002619 0.365290 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3442 3476 -0.012528 -0.053588 2.996099 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3445 3477 -0.001225 0.016374 -0.269513 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3431 3478 -1.022450 0.018633 -0.099748 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3415 3479 0.036866 0.014549 -2.865191 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3416 3480 0.007039 -0.039743 0.098655 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3437 3481 -0.010448 0.001084 3.010846 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3433 3481 0.004163 -0.020544 -0.283537 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3420 3482 0.003153 0.032379 -2.948294 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3419 3483 0.064131 -0.020825 -0.048135 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3435 3484 0.017613 -1.016570 -1.783357 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3436 3485 -1.032430 2.011510 1.629042 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3411 3487 3.993780 0.013439 -1.665790 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3409 3491 1.966110 0.010055 -3.059549 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3412 3491 -0.999288 -0.006317 1.374544 89.442719 0.000000 89.442719 21.073235 0.000000 0.000000
-EDGE2 3404 3496 -1.022640 -3.001550 1.778102 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3403 3497 2.001320 0.041642 3.005657 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3404 3498 -1.010340 -1.019740 1.545056 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3405 3498 -2.018110 -1.032670 1.509127 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3403 3499 -0.031191 0.017659 -2.944473 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
-EDGE2 3402 3499 1.022250 0.034739 3.081548 44.721360 0.000000 44.721360 16.035746 0.000000 0.000000
diff --git a/demos/maps/map_apriltag_logitech_1234.yaml b/demos/maps/map_apriltag_logitech_1234.yaml
deleted file mode 100644
index f313d1a11..000000000
--- a/demos/maps/map_apriltag_logitech_1234.yaml
+++ /dev/null
@@ -1,46 +0,0 @@
-map name: "4 tags printed on a A4 sheet vertical recorded at IRI with logitech webcam."
-
-nlandmarks: 4 # This must match the number of landmarks in the list that follows. Otherwise it is an error.
-
-######################
-# World frame is considered to be the top left corner of tag id 0. Reference frame is corherent with a camera
-# looking straight at the sheet with RBF convention.
-######################
-landmarks:
-
- - id : 0 # use same as tag id
- type: "APRILTAG" # This must match the KEY used in the LandmarkFactory. Otherwise it is an error.
- tag id: 0
- tag width: 0.055
- position: [0.0225, 0.0225, 0]
- orientation: [0, 0, 0] # roll pitch yaw in degrees
- position fixed: true
- orientation fixed: true
-
- - id : 1 # use same as tag id
- type: "APRILTAG" # This must match the KEY used in the LandmarkFactory. Otherwise it is an error.
- tag id: 1
- tag width: 0.055
- position: [0.1525, 0.0225, 0]
- orientation: [0, 0, 0] # roll pitch yaw in degrees
- position fixed: true
- orientation fixed: true
-
- - id : 2 # use same as tag id
- type: "APRILTAG" # This must match the KEY used in the LandmarkFactory. Otherwise it is an error.
- tag id: 2
- tag width: 0.055
- position: [0.0225, 0.2125, 0]
- orientation: [0, 0, 0] # roll pitch yaw in degrees
- position fixed: true
- orientation fixed: true
-
- - id : 3 # use same as tag id
- type: "APRILTAG" # This must match the KEY used in the LandmarkFactory. Otherwise it is an error.
- tag id: 3
- tag width: 0.055
- position: [0.1525, 0.2125, 0]
- orientation: [0, 0, 0] # roll pitch yaw in degrees
- position fixed: true
- orientation fixed: true
-
diff --git a/demos/solver/test_SPQR.cpp b/demos/solver/test_SPQR.cpp
deleted file mode 100644
index 04592dbd0..000000000
--- a/demos/solver/test_SPQR.cpp
+++ /dev/null
@@ -1,92 +0,0 @@
-/*
- * test_SPQR.cpp
- *
- * Created on: Jun 18, 2015
- * Author: jvallve
- */
-
-#include <iostream>
-#include <eigen3/Eigen/SPQRSupport>
-#include <eigen3/Eigen/CholmodSupport>
-#include "SuiteSparseQR.hpp"
-
-using namespace Eigen;
-
-int main (int argc, char **argv)
-{
- ///////////////////////////////////////////////////////////////////////
- // Eigen Support SPQR
- SPQR < SparseMatrix<double> > solver;
- //solver.setSPQROrdering(0); // no ordering -> segmentation fault
-
- SparseMatrix<double> matA(4,3);
- matA.coeffRef(0,0) = 0.1;
- matA.coeffRef(1,0) = 0.4;
- matA.coeffRef(1,1) = 0.2;
- matA.coeffRef(2,1) = 0.4;
- matA.coeffRef(2,2) = 0.2;
- matA.coeffRef(3,2) = 0.1;
-
- std::cout << "matA: " << std::endl << matA << std::endl;
-
- VectorXd b_ = VectorXd::Ones(4);
- VectorXd x_(3);
-
- std::cout << "b_: " << std::endl << b_ << std::endl;
-
- solver.compute(matA);
- if (solver.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- std::cout << "R: " << std::endl << solver.matrixR() << std::endl;
- x_ = solver.solve(b_);
- std::cout << "solved x_" << std::endl << x_ << std::endl;
- std::cout << "ordering: " << solver.colsPermutation().indices().transpose() << std::endl;
-
- ///////////////////////////////////////////////////////////////////////
- // Directly in suitesparse
- cholmod_common Common, *cc ;
- cholmod_sparse A ;
- cholmod_dense *X, *B, *Residual ;
- double rnorm, one [2] = {1,0}, minusone [2] = {-1,0} ;
- int mtype ;
-
- // start CHOLMOD
- cc = &Common ;
- cholmod_l_start (cc) ;
-
- // load A
- A = viewAsCholmod(matA);
- //A = (cholmod_sparse *) cholmod_l_read_matrix (stdin, 1, &mtype, cc) ;
- std::cout << "A.xtype " << A.xtype << std::endl;
- std::cout << "A.nrow " << A.nrow << std::endl;
- std::cout << "A.ncol " << A.ncol << std::endl;
-
- // B = ones (size (A,1),1)
- B = cholmod_l_ones (A.nrow, 1, A.xtype, cc) ;
-
- std::cout << "2" << std::endl;
- // X = A\B
- //X = SuiteSparseQR <double> (0, SPQR_DEFAULT_TOL, &A, B, cc) ;
- X = SuiteSparseQR <double> (&A, B, cc);
-
- std::cout << "3" << std::endl;
- // rnorm = norm (B-A*X)
- Residual = cholmod_l_copy_dense (B, cc) ;
- std::cout << "4" << std::endl;
- cholmod_l_sdmult (&A, 0, minusone, one, X, Residual, cc) ;
- std::cout << "5" << std::endl;
- rnorm = cholmod_l_norm_dense (Residual, 2, cc) ;
- printf ("2-norm of residual: %8.1e\n", rnorm) ;
- printf ("rank %ld\n", cc->SPQR_istat [4]) ;
-
- // free everything and finish CHOLMOD
- cholmod_l_free_dense (&Residual, cc) ;
- //cholmod_l_free_sparse (A, cc) ;
- cholmod_l_free_dense (&X, cc) ;
- cholmod_l_free_dense (&B, cc) ;
- cholmod_l_finish (cc) ;
- return (0) ;
-}
diff --git a/demos/solver/test_ccolamd.cpp b/demos/solver/test_ccolamd.cpp
deleted file mode 100644
index d9eec5b00..000000000
--- a/demos/solver/test_ccolamd.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/*
- * test_ccolamd.cpp
- *
- * Created on: Jun 11, 2015
- * Author: jvallve
- */
-
-// Wolf includes
-#include "base/common/wolf.h"
-
-//std includes
-#include <cstdlib>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// ccolamd
-#include "solver/ccolamd_ordering.h"
-
-// eigen includes
-#include <eigen3/Eigen/OrderingMethods>
-#include <eigen3/Eigen/CholmodSupport>
-#include <eigen3/Eigen/SparseLU>
-
-using namespace Eigen;
-using namespace wolf;
-
-//main
-int main(int argc, char *argv[])
-{
- if (argc != 2 || atoi(argv[1]) < 1)
- {
- std::cout << "Please call me with: [./test_ccolamd SIZE], where:" << std::endl;
- std::cout << " - SIZE: integer size of the problem" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
- SizeEigen size = atoi(argv[1]);
-
- SparseMatrix<double, ColMajor, SizeEigen> A(size, size), Aordered(size, size);
- CholmodSupernodalLLT < SparseMatrix<double, ColMajor, SizeEigen> > solver;
- PermutationMatrix<Dynamic, Dynamic, SizeEigen> perm(size);
- CCOLAMDOrdering<SizeEigen> ordering;
- Matrix<SizeEigen, Dynamic, 1> ordering_factors = Matrix<SizeEigen, Dynamic, 1>::Ones(size);
- VectorXd b(size), bordered(size), xordered(size), x(size);
- clock_t t1, t2, t3;
- double time1, time2, time3;
-
- // BUILD THE PROBLEM ----------------------------
- //Fill A & b
- A.insert(0, 0) = 5;
- b(0) = 1;
- for (int i = 1; i < size; i++)
- {
- A.insert(i, i) = 5;
- A.insert(i, i - 1) = 1;
- A.insert(i - 1, i) = 1;
- b(i) = i + 1;
- }
- A.insert(size - 1, 0) = 2;
- A.insert(0, size - 1) = 2;
-
- std::cout << "Solving Ax = b:" << std::endl << "A = " << std::endl << A << std::endl << std::endl;
- std::cout << "b = " << std::endl << b.transpose() << std::endl << std::endl;
-
- // SOLVING WITHOUT REORDERING ------------------------------------
- // solve Ax = b
- t1 = clock();
- solver.compute(A);
- if (solver.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x = solver.solve(b);
- time1 = ((double) clock() - t1) / CLOCKS_PER_SEC;
- std::cout << "solved in " << time1 << "seconds" << std::endl;
- std::cout << "x = " << x.transpose() << std::endl;
-
- // SOLVING AFTER REORDERING ------------------------------------
- // ordering factors
- ordering_factors(size-1) = 2;
- ordering_factors(0) = 2;
-
- // ordering
- t2 = clock();
- A.makeCompressed();
-
- std::cout << "Reordering using CCOLAMD:" << std::endl;
- std::cout << "ordering_factors = " << std::endl << ordering_factors.transpose() << std::endl << std::endl;
- ordering(A, perm, ordering_factors.data());
- std::cout << "perm = " << std::endl << perm.indices().transpose() << std::endl << std::endl;
-
- bordered = perm * b;
- Aordered = A.twistedBy(perm);
- std::cout << "reordered A = " << std::endl << Aordered * MatrixXd::Identity(size, size) << std::endl << std::endl;
- std::cout << "reordered b = " << std::endl << bordered.transpose() << std::endl << std::endl;
-
- // solve Ax = b
- solver.compute(Aordered);
- if (solver.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- xordered = solver.solve(bordered);
- time2 = ((double) clock() - t2) / CLOCKS_PER_SEC;
- std::cout << "solved in " << time2 << "seconds" << std::endl;
- std::cout << "x = " << (perm.inverse() * xordered).transpose() << std::endl;
- std::cout << "x = " << x.transpose() << " (solution without reordering)" << std::endl;
-
- // SOLVING AND REORDERING ------------------------------------
- t3 = clock();
- SparseLU<SparseMatrix<double, ColMajor, SizeEigen>, CCOLAMDOrdering<SizeEigen> > solver2;
- solver2.compute(A);
- if (solver2.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x = solver2.solve(b);
- time3 = ((double) clock() - t3) / CLOCKS_PER_SEC;
- std::cout << "solved in " << time3 << "seconds" << std::endl;
- std::cout << "x = " << x.transpose() << std::endl;
-}
-
diff --git a/demos/solver/test_ccolamd_blocks.cpp b/demos/solver/test_ccolamd_blocks.cpp
deleted file mode 100644
index 83cc7af84..000000000
--- a/demos/solver/test_ccolamd_blocks.cpp
+++ /dev/null
@@ -1,180 +0,0 @@
-/*
- * test_ccolamd_blocks.cpp
- *
- * Created on: Jun 12, 2015
- * Author: jvallve
- */
-
-//std includes
-#include <cstdlib>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// eigen includes
-#include <eigen3/Eigen/OrderingMethods>
-#include <eigen3/Eigen/CholmodSupport>
-#include <eigen3/Eigen/SparseLU>
-
-// ccolamd
-#include "solver/ccolamd_ordering.h"
-
-using namespace Eigen;
-
-void eraseSparseBlock(SparseMatrix<double>& original, const unsigned int& row, const unsigned int& Nrows, const unsigned int& col, const unsigned int& Ncols)
-{
- for (unsigned int i = row; i < row + Nrows; i++)
- for (unsigned int j = col; j < row + Ncols; j++)
- original.coeffRef(i,j) = 0.0;
-
- original.makeCompressed();
-}
-
-void addSparseBlock(const MatrixXd& ins, SparseMatrix<double>& original, const unsigned int& row, const unsigned int& col)
-{
- for (unsigned int r=0; r<ins.rows(); ++r)
- for (unsigned int c = 0; c < ins.cols(); c++)
- original.coeffRef(r + row, c + col) += ins(r,c);
-}
-
-void permutation_2_block_permutation(const PermutationMatrix<Dynamic, Dynamic, int> &perm, PermutationMatrix<Dynamic, Dynamic, int> &perm_blocks, const int dim, const int size)
-{
- ArrayXXi idx(dim, size);
- idx.row(0) = dim * perm.indices().transpose();
- for (int i = 1; i<dim; i++)
- idx.row(i) = idx.row(i-1) + 1;
- Map<ArrayXi> idx_blocks(idx.data(), dim*size, 1);
- perm_blocks.indices() = idx_blocks;
-}
-
-//main
-int main(int argc, char *argv[])
-{
- if (argc != 3 || atoi(argv[1]) < 1|| atoi(argv[2]) < 1)
- {
- std::cout << "Please call me with: [./test_ccolamd SIZE DIM], where:" << std::endl;
- std::cout << " - SIZE: integer size of the problem" << std::endl;
- std::cout << " - DIM: integer dimension of the nodes" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
- int size = atoi(argv[1]);
- int dim = atoi(argv[2]);
-
- SparseMatrix<double> H(size * dim, size * dim), H_ordered(size * dim, size * dim), H_block_ordered(size * dim, size * dim);
- SparseMatrix<int> FactorMatrix(size,size);
- CholmodSupernodalLLT < SparseMatrix<double> > solver, solver2, solver3;
- PermutationMatrix<Dynamic, Dynamic, int> perm(size), perm_blocks(size * dim);
- CCOLAMDOrdering<int> ordering;
- VectorXi block_ordering_factors = VectorXi::Ones(size);
- VectorXi ordering_factors = VectorXi::Ones(size*dim);
- VectorXd b(size * dim), b_ordered(size * dim), b_block_ordered(size * dim), x_block_ordered(size * dim), x_ordered(size * dim), x(size * dim);
- clock_t t1, t2, t3;
- double time1, time2, time3;
-
- MatrixXd omega = MatrixXd::Constant(dim, dim, 0.1) + MatrixXd::Identity(dim, dim);
-
- // BUILD THE PROBLEM ----------------------------
- //Fill H & b
- for (int i = 0; i < size; i++)
- {
- addSparseBlock(5*omega, H, i*dim, i*dim);
- FactorMatrix.insert(i,i) = 1;
- if (i > 0)
- {
- addSparseBlock(omega, H, i*dim, (i-1)*dim);
- addSparseBlock(omega, H, (i-1)*dim, i*dim);
- FactorMatrix.insert(i,i-1) = 1;
- FactorMatrix.insert(i-1,i) = 1;
- }
- b.segment(i*dim, dim) = VectorXd::Constant(dim, i+1);
- }
- addSparseBlock(2*omega, H, 0, (size - 1)*dim);
- addSparseBlock(2*omega, H, (size-1)*dim, 0);
- FactorMatrix.insert(0,size-1) = 1;
- FactorMatrix.insert(size-1,0) = 1;
-
- std::cout << "Solving factor graph:" << std::endl;
- std::cout << "Factors: " << std::endl << FactorMatrix * MatrixXi::Identity(size,size) << std::endl << std::endl;
-
- // SOLVING WITHOUT REORDERING ------------------------------------
- // solve Hx = b
- t1 = clock();
- solver.compute(H);
- if (solver.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x = solver.solve(b);
- time1 = ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // SOLVING AFTER REORDERING ------------------------------------
- // ordering factors
- ordering_factors.segment(dim * (size-1), dim) = VectorXi::Constant(dim,2);
- ordering_factors.segment(0, dim) = VectorXi::Constant(dim,2);
-
- // variable ordering
- t2 = clock();
- H.makeCompressed();
-
- std::cout << "Reordering using CCOLAMD:" << std::endl;
- std::cout << "ordering_factors = " << std::endl << ordering_factors.transpose() << std::endl << std::endl;
- ordering(H, perm, ordering_factors.data());
-
- b_ordered = perm * b;
- H_ordered = H.twistedBy(perm);
-
- // solve Hx = b
- solver2.compute(H_ordered);
- if (solver2.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x_ordered = solver2.solve(b_ordered);
- x_ordered = perm.inverse() * x_ordered;
- time2 = ((double) clock() - t2) / CLOCKS_PER_SEC;
-
- // SOLVING AFTER BLOCK REORDERING ------------------------------------
- // ordering factors
- block_ordering_factors(size-1) = 2;
- block_ordering_factors(0) = 2;
-
- // block ordering
- t3 = clock();
- FactorMatrix.makeCompressed();
-
- std::cout << "Reordering using Block CCOLAMD:" << std::endl;
- std::cout << "block_ordering_factors = " << std::endl << block_ordering_factors.transpose() << std::endl << std::endl;
- ordering(FactorMatrix, perm_blocks, block_ordering_factors.data());
-
- // variable ordering
- permutation_2_block_permutation(perm_blocks, perm , dim, size);
- b_block_ordered = perm * b;
- H_block_ordered = H.twistedBy(perm);
-
- // solve Hx = b
- solver3.compute(H_block_ordered);
- if (solver3.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x_block_ordered = solver3.solve(b_block_ordered);
- x_block_ordered = perm.inverse() * x_block_ordered;
- time3 = ((double) clock() - t3) / CLOCKS_PER_SEC;
-
- // RESULTS ------------------------------------
- std::cout << "NO REORDERING: solved in " << time1*1e3 << " ms" << std::endl;
- std::cout << "REORDERING: solved in " << time2*1e3 << " ms" << std::endl;
- std::cout << "BLOCK REORDERING: solved in " << time3*1e3 << " ms" << std::endl;
- //std::cout << "x = " << x.transpose() << std::endl;
- //std::cout << "x = " << x_ordered.transpose() << std::endl;
- //std::cout << "x = " << x_block_ordered.transpose() << std::endl;
-}
-
diff --git a/demos/solver/test_iQR.cpp b/demos/solver/test_iQR.cpp
deleted file mode 100644
index b027c874d..000000000
--- a/demos/solver/test_iQR.cpp
+++ /dev/null
@@ -1,350 +0,0 @@
-/*
- * test_iQR.cpp
- *
- * Created on: Jun 17, 2015
- * Author: jvallve
- */
-
-/*
- * test_ccolamd_blocks.cpp
- *
- * Created on: Jun 12, 2015
- * Author: jvallve
- */
-
-//std includes
-#include <cstdlib>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// eigen includes
-#include <eigen3/Eigen/OrderingMethods>
-#include <eigen3/Eigen/SparseQR>
-#include <eigen3/Eigen/SPQRSupport>
-
-// ccolamd
-#include "solver/ccolamd_ordering.h"
-
-using namespace Eigen;
-
-class block_pruning
-{
- public:
- int col, row, Nrows, Ncols;
- block_pruning(int _col, int _row, int _Nrows, int _Ncols) :
- col(_col),
- row(_row),
- Nrows(_Nrows),
- Ncols(_Ncols)
- {
- //
- }
- bool operator()(int i, int j, double) const
- {
- return (i < row || i > row + Nrows-1) || (j < col || j > col + Ncols-1);
- }
-};
-
-void eraseSparseBlock(SparseMatrix<double>& original, const unsigned int& row, const unsigned int& col, const unsigned int& Nrows, const unsigned int& Ncols)
-{
- // prune all non-zero elements that not satisfy the 'keep' operand
- // elements that are not in the block rows or are not in the block columns should be kept
- //original.prune([](int i, int j, double) { return (i < row || i > row + Nrows-1) || (j < col || j > col + Ncols-1); });
-
- block_pruning bp(row, col, Nrows, Ncols);
- original.prune(bp);
-
-// for (unsigned int i = row; i < row + Nrows; i++)
-// for (unsigned int j = col; j < row + Ncols; j++)
-// original.coeffRef(i,j) = 0.0;
-//
-// original.prune(0);
-}
-
-void addSparseBlock(const MatrixXd& ins, SparseMatrix<double>& original, const unsigned int& row, const unsigned int& col)
-{
- for (unsigned int r=0; r<ins.rows(); ++r)
- for (unsigned int c = 0; c < ins.cols(); c++)
- if (ins(r,c) != 0)
- original.coeffRef(r + row, c + col) += ins(r,c);
-}
-
-void permutation_2_block_permutation(const PermutationMatrix<Dynamic, Dynamic, int> &perm_nodes, PermutationMatrix<Dynamic, Dynamic, int> &perm_variables, const int dim)
-{
- ArrayXXi idx(dim, perm_nodes.indices().rows());
- idx.row(0) = dim * perm_nodes.indices().transpose();
-
- for (int i = 1; i<dim; i++)
- idx.row(i) = idx.row(i-1) + 1;
- Map<ArrayXi> idx_blocks(idx.data(), dim*perm_nodes.indices().rows(), 1);
- perm_variables.indices() = idx_blocks;
-}
-
-void augment_permutation(PermutationMatrix<Dynamic, Dynamic, int> &perm, const int new_size)
-{
- int old_size = perm.indices().size();
- int dim = new_size - old_size;
- VectorXi new_indices(new_size);
- new_indices.head(old_size)= perm.indices();
- new_indices.tail(dim) = ArrayXi::LinSpaced(dim, old_size, new_size-1);
- perm.resize(new_size);
- perm.indices() = new_indices;
-}
-
-//main
-int main(int argc, char *argv[])
-{
- if (argc != 3 || atoi(argv[1]) < 1|| atoi(argv[2]) < 1)
- {
- std::cout << "Please call me with: [./test_iQR SIZE DIM], where:" << std::endl;
- std::cout << " - SIZE: integer size of the problem" << std::endl;
- std::cout << " - DIM: integer dimension of the nodes" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
- int size = atoi(argv[1]);
- int dim = atoi(argv[2]);
-
- // Problem variables
- SparseQR < SparseMatrix<double>, NaturalOrdering<int>> solver_ordered, solver_unordered, solver_ordered_partial;
-
- MatrixXd omega = MatrixXd::Constant(dim, dim, 0.1) + MatrixXd::Identity(dim, dim);
- SparseMatrix<double> A(0,0),
- A_ordered(0,0),
- R(0,0);
- VectorXd b,
- x,
- x_ordered,
- x_ordered_partial;
- int n_measurements = 0;
- int n_nodes = 0;
-
- // ordering variables
- SparseMatrix<int> A_nodes_ordered(0,0);
- PermutationMatrix<Dynamic, Dynamic, int> acc_permutation_nodes_matrix(0);
-
- CCOLAMDOrdering<int> ordering, partial_ordering;
- VectorXi nodes_ordering_factors;
-
- // results variables
- clock_t t_ordering, t_solving_ordered_full, t_solving_unordered, t_solving_ordered_partial, t4;
- double time_ordering=0, time_solving_unordered=0, time_solving_ordered=0, time_solving_ordered_partial=0;
-
- std::cout << "STARTING INCREMENTAL QR TEST" << std::endl << std::endl;
-
- // GENERATING MEASUREMENTS
- std::vector<std::vector<int>> measurements;
- for (int i = 0; i < size; i++)
- {
- std::vector<int> meas(0);
- if (i == 0) //prior
- {
- meas.push_back(0);
- measurements.push_back(meas);
- meas.clear();
- }
- else //odometry
- {
- meas.push_back(i-1);
- meas.push_back(i);
- measurements.push_back(meas);
- meas.clear();
- }
- if (i > size / 2) // loop closures
- {
- meas.push_back(0);
- meas.push_back(i);
- measurements.push_back(meas);
- meas.clear();
- }
- }
-
- // INCREMENTAL LOOP
- for (unsigned int i = 0; i < measurements.size(); i++)
- {
- std::cout << "========================= MEASUREMENT " << i << ":" << std::endl;
- std::vector<int> measurement = measurements.at(i);
-
- // AUGMENT THE PROBLEM ----------------------------
- n_measurements++;
- while (n_nodes < measurement.back()+1)
- {
- n_nodes++;
- // Resize accumulated permutations
- augment_permutation(acc_permutation_nodes_matrix, n_nodes);
-
- // Resize state
- x.conservativeResize(n_nodes*dim);
- x_ordered.conservativeResize(n_nodes*dim);
- x_ordered_partial.conservativeResize(n_nodes*dim);
- }
- A.conservativeResize(n_measurements*dim,n_nodes*dim);
- A_ordered.conservativeResize(n_measurements*dim,n_nodes*dim);
- R.conservativeResize(n_nodes*dim,n_nodes*dim);
- b.conservativeResize(n_measurements*dim);
- A_nodes_ordered.conservativeResize(n_measurements,n_nodes);
-
- // ADD MEASUREMENTS
- int min_ordered_node = n_nodes;
- for (unsigned int j = 0; j < measurement.size(); j++)
- {
- int ordered_node = acc_permutation_nodes_matrix.indices()(measurement.at(j));
-
- addSparseBlock(2*omega, A, A.rows()-dim, measurement.at(j) * dim);
- addSparseBlock(2*omega, A_ordered, A_ordered.rows()-dim, ordered_node * dim);
-
- A_nodes_ordered.coeffRef(A_nodes_ordered.rows()-1, ordered_node) = 1;
-
- b.segment(b.size() - dim, dim) = VectorXd::LinSpaced(dim, b.size()-dim, b.size()-1);
- // store minimum ordered node
- if (min_ordered_node > ordered_node)
- min_ordered_node = ordered_node;
- }
-
-// std::cout << "Solving Ax = b" << std::endl;
-// std::cout << "A_nodes_ordered: " << std::endl << MatrixXi::Identity(A_nodes_ordered.rows(), A_nodes_ordered.rows()) * A_nodes_ordered << std::endl << std::endl;
-// std::cout << "A: " << std::endl << MatrixXd::Identity(A.rows(), A.rows()) * A << std::endl << std::endl;
-// std::cout << "A_ordered: " << std::endl << MatrixXd::Identity(A.rows(), A.rows()) * A_ordered << std::endl << std::endl;
-// std::cout << "b: " << std::endl << b.transpose() << std::endl << std::endl;
-
- // BLOCK REORDERING ------------------------------------
- t_ordering = clock();
- int ordered_nodes = n_nodes - min_ordered_node;
- int unordered_nodes = n_nodes - ordered_nodes;
- if (n_nodes > 1 && ordered_nodes > 2) // only reordering when involved nodes in the measurement are not the two last ones
- {
- // SUBPROBLEM ORDERING (from first node variable to last one)
- std::cout << "ordering partial problem: " << min_ordered_node << " to "<< n_nodes - 1 << std::endl;
- SparseMatrix<int> sub_A_nodes_ordered = A_nodes_ordered.rightCols(ordered_nodes);
-
- // partial ordering factors
- VectorXi nodes_partial_ordering_factors = sub_A_nodes_ordered.bottomRows(1).transpose();
-
- // computing nodes partial ordering
- A_nodes_ordered.makeCompressed();
- PermutationMatrix<Dynamic, Dynamic, int> partial_permutation_nodes_matrix(ordered_nodes);
- partial_ordering(sub_A_nodes_ordered, partial_permutation_nodes_matrix, nodes_partial_ordering_factors.data());
-
- // node ordering to variable ordering
- PermutationMatrix<Dynamic, Dynamic, int> partial_permutation_matrix(A_ordered.cols());
- permutation_2_block_permutation(partial_permutation_nodes_matrix, partial_permutation_matrix , dim);
-
- // apply partial orderings
- A_nodes_ordered.rightCols(ordered_nodes) = (A_nodes_ordered.rightCols(ordered_nodes) * partial_permutation_nodes_matrix.transpose()).sparseView();
- A_ordered.rightCols(ordered_nodes * dim) = (A_ordered.rightCols(ordered_nodes * dim) * partial_permutation_matrix.transpose()).sparseView();
- R.rightCols(ordered_nodes * dim) = (R.rightCols(ordered_nodes * dim) * partial_permutation_matrix.transpose()).sparseView();
-
- // ACCUMULATING PERMUTATIONS
- PermutationMatrix<Dynamic, Dynamic, int> permutation_nodes_matrix(VectorXi::LinSpaced(n_nodes, 0, n_nodes - 1)); // identity permutation
- permutation_nodes_matrix.indices().tail(ordered_nodes) = partial_permutation_nodes_matrix.indices() + VectorXi::Constant(ordered_nodes, n_nodes - ordered_nodes);
- acc_permutation_nodes_matrix = permutation_nodes_matrix * acc_permutation_nodes_matrix;
- }
- time_ordering += ((double) clock() - t_ordering) / CLOCKS_PER_SEC;
- // std::cout << "incrementally ordered A Block structure: " << std::endl << MatrixXi::Identity(A_nodes_ordered.rows(), A_nodes_ordered.rows()) * A_nodes_ordered << std::endl << std::endl;
- //std::cout << "ordered A: " << std::endl << MatrixXd::Identity(A_ordered.rows(), A_ordered.rows()) * A_ordered << std::endl << std::endl;
- //std::cout << "b: " << std::endl << b.transpose() << std::endl << std::endl;
-
- // SOLVING
- // solving ordered subproblem
- t_solving_ordered_partial = clock();
- A_nodes_ordered.makeCompressed();
- A_ordered.makeCompressed();
-
- // finding measurements block
- SparseMatrix<int> measurements_to_initial = A_nodes_ordered.col(min_ordered_node);
-// std::cout << "measurements_to_initial " << measurements_to_initial << std::endl;
-// std::cout << "measurements_to_initial.innerIndex()[measurements_to_initial.outerIndex()[0]] " << measurements_to_initial.innerIndex()[measurements_to_initial.outerIndex()[0]] << std::endl;
- int initial_measurement = measurements_to_initial.innerIndex()[measurements_to_initial.outerIndex()[0]];
-
- SparseMatrix<double> A_ordered_partial = A_ordered.bottomRightCorner((n_nodes - initial_measurement) * dim, ordered_nodes * dim);
- solver_ordered_partial.compute(A_ordered_partial);
- if (solver_ordered_partial.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- std::cout << "R new" << std::endl << MatrixXd::Identity(ordered_nodes * dim, ordered_nodes * dim) * solver_ordered_partial.matrixR() << std::endl;
- x_ordered_partial.tail(ordered_nodes * dim) = solver_ordered_partial.solve(b.tail(ordered_nodes * dim));
- std::cout << "x_ordered_partial.tail(ordered_nodes * dim)" << std::endl << x_ordered_partial.tail(ordered_nodes * dim).transpose() << std::endl;
- // store new part of R (equivalent to R.bottomRightCorner(ordered_nodes * dim, ordered_nodes * dim) = solver3.matrixR();)
- eraseSparseBlock(R, unordered_nodes * dim, unordered_nodes * dim, ordered_nodes * dim, ordered_nodes * dim);
- addSparseBlock(solver_ordered_partial.matrixR(), R, unordered_nodes * dim, unordered_nodes * dim);
- std::cout << "R" << std::endl << MatrixXd::Identity(R.rows(), R.rows()) * R << std::endl;
- R.makeCompressed();
-
- // solving not ordered subproblem
- if (unordered_nodes > 0)
- {
- std::cout << "--------------------- solving unordered part" << std::endl;
- SparseMatrix<double> R1 = R.topLeftCorner(unordered_nodes * dim, unordered_nodes * dim);
- std::cout << "R1" << std::endl << MatrixXd::Identity(R1.rows(), R1.rows()) * R1 << std::endl;
- SparseMatrix<double> R2 = R.topRightCorner(unordered_nodes * dim, ordered_nodes * dim);
- std::cout << "R2" << std::endl << MatrixXd::Identity(R2.rows(), R2.rows()) * R2 << std::endl;
- solver_ordered_partial.compute(R1);
- if (solver_ordered_partial.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x_ordered_partial.head(unordered_nodes * dim) = solver_ordered_partial.solve(b.head(unordered_nodes * dim) - R2 * x_ordered_partial.tail(ordered_nodes * dim));
- }
- // undo ordering
- PermutationMatrix<Dynamic, Dynamic, int> acc_permutation_matrix(A_ordered.cols());
- permutation_2_block_permutation(acc_permutation_nodes_matrix, acc_permutation_matrix , dim);
- x_ordered_partial = acc_permutation_matrix.inverse() * x_ordered_partial;
- time_solving_ordered_partial += ((double) clock() - t_solving_ordered_partial) / CLOCKS_PER_SEC;
-
- // SOLVING
- // full ordered problem
- t_solving_ordered_full = clock();
- A_nodes_ordered.makeCompressed();
- A_ordered.makeCompressed();
- solver_ordered.compute(A_ordered);
- if (solver_ordered.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x_ordered = solver_ordered.solve(b);
- std::cout << "solver_ordered.matrixR()" << std::endl << MatrixXd::Identity(A_ordered.cols(), A_ordered.cols()) * solver_ordered.matrixR() << std::endl;
- // undo ordering
- PermutationMatrix<Dynamic, Dynamic, int> acc_permutation_matrix2(A_ordered.cols());
- permutation_2_block_permutation(acc_permutation_nodes_matrix, acc_permutation_matrix2 , dim);
- x_ordered = acc_permutation_matrix.inverse() * x_ordered;
- time_solving_ordered += ((double) clock() - t_solving_ordered_full) / CLOCKS_PER_SEC;
-
- // WITHOUT ORDERING
- t_solving_unordered = clock();
- A.makeCompressed();
- solver_unordered.compute(A);
- if (solver_unordered.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- //std::cout << "no ordering? " << solver_unordered.colsPermutation().indices().transpose() << std::endl;
- x = solver_unordered.solve(b);
- std::cout << "solver_unordered.matrixR()" << std::endl << MatrixXd::Identity(A.cols(), A.cols()) * solver_unordered.matrixR() << std::endl;
- time_solving_unordered += ((double) clock() - t_solving_unordered) / CLOCKS_PER_SEC;
-
- // RESULTS ------------------------------------
- std::cout << "========================= RESULTS " << i << ":" << std::endl;
- std::cout << "NO REORDERING: solved in " << time_solving_unordered*1e3 << " ms | " << solver_unordered.matrixR().nonZeros() << " nonzeros in R"<< std::endl;
- std::cout << "BLOCK REORDERING: solved in " << time_solving_ordered*1e3 << " ms | " << solver_ordered.matrixR().nonZeros() << " nonzeros in R"<< std::endl;
- std::cout << "BLOCK REORDERING 2: solved in " << time_solving_ordered_partial*1e3 << " ms | " << R.nonZeros() << " nonzeros in R"<< std::endl;
-
- std::cout << "x = " << x.transpose() << std::endl;
- std::cout << "x_ordered = " << x_ordered.transpose() << std::endl;
- std::cout << "x_ordered_partial = " << x_ordered_partial.transpose() << std::endl;
- if ((x_ordered_partial-x_ordered).maxCoeff() < 1e-10)
- std::cout << "Both solutions are equals (tolerance " << (x_ordered_partial-x_ordered).maxCoeff() << ")" << std::endl;
- else
- std::cout << "DIFFERENT SOLUTIONS!!!!!!!! max difference " << (x_ordered_partial-x_ordered).maxCoeff() << std::endl;
- }
-}
-
diff --git a/demos/solver/test_iQR_wolf.cpp b/demos/solver/test_iQR_wolf.cpp
deleted file mode 100644
index 2fdc1f9f2..000000000
--- a/demos/solver/test_iQR_wolf.cpp
+++ /dev/null
@@ -1,560 +0,0 @@
-/*
- * test_iQR_wolf.cpp
- *
- * Created on: Jun 17, 2015
- * Author: jvallve
- */
-
-//std includes
-#include <cstdlib>
-#include <string>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// eigen includes
-#include <eigen3/Eigen/OrderingMethods>
-#include <eigen3/Eigen/SparseQR>
-#include <Eigen/SPQRSupport>
-
-// ccolamd
-#include "solver/ccolamd_ordering.h"
-
-using namespace Eigen;
-
-class block_pruning
-{
- public:
- int col, row, Nrows, Ncols;
- block_pruning(int _col, int _row, int _Nrows, int _Ncols) :
- col(_col),
- row(_row),
- Nrows(_Nrows),
- Ncols(_Ncols)
- {
- //
- }
- bool operator()(int i, int j, double) const
- {
- return (i < row || i > row + Nrows-1) || (j < col || j > col + Ncols-1);
- }
-};
-
-void eraseSparseBlock(SparseMatrix<double, ColMajor>& original, const unsigned int& row, const unsigned int& col, const unsigned int& Nrows, const unsigned int& Ncols)
-{
- // prune all non-zero elements that not satisfy the 'keep' operand
- // elements that are not in the block rows or are not in the block columns should be kept
- //original.prune([](int i, int j, double) { return (i < row || i > row + Nrows-1) || (j < col || j > col + Ncols-1); });
-
- block_pruning bp(row, col, Nrows, Ncols);
- original.prune(bp);
-
-// for (unsigned int i = row; i < row + Nrows; i++)
-// for (unsigned int j = col; j < row + Ncols; j++)
-// original.coeffRef(i,j) = 0.0;
-//
-// original.prune(0);
-}
-
-void addSparseBlock(const MatrixXd& ins, SparseMatrix<double, ColMajor>& original, const unsigned int& row, const unsigned int& col)
-{
- for (unsigned int r=0; r<ins.rows(); ++r)
- for (unsigned int c = 0; c < ins.cols(); c++)
- if (ins(r,c) != 0)
- original.coeffRef(r + row, c + col) += ins(r,c);
-}
-
-struct node
-{
- public:
- int id;
- int dim;
- int location;
- int order;
-
- node(const int _id, const int _dim, const int _location, const int _order) :
- id(_id),
- dim(_dim),
- location(_location),
- order(_order)
- {
-
- }
-};
-
-struct measurement
-{
- public:
- std::vector<MatrixXd> jacobians;
- std::vector<int> nodes_idx;
- VectorXd error;
- int dim;
- bool odometry_type;
- int location;
-
- measurement(const MatrixXd & _jacobian1, const int _idx1, const VectorXd &_error, const int _meas_dim, bool _odometry_type=false) :
- jacobians({_jacobian1}),
- nodes_idx({_idx1}),
- error(_error),
- dim(_meas_dim),
- odometry_type(_odometry_type),
- location(0)
- {
- //jacobians.push_back(_jacobian1);
- }
-
- measurement(const MatrixXd & _jacobian1, const int _idx1, const MatrixXd & _jacobian2, const int _idx2, const VectorXd &_error, const int _meas_dim, bool _odometry_type=false) :
- jacobians({_jacobian1, _jacobian2}),
- nodes_idx({_idx1, _idx2}),
- error(_error),
- dim(_meas_dim),
- odometry_type(_odometry_type),
- location(0)
- {
-
- }
-};
-
-class SolverQR
-{
- protected:
- std::string name_;
- SparseQR < SparseMatrix<double, ColMajor>, NaturalOrdering<int>> solver_;
- SparseMatrix<double, ColMajor> A_, R_;
- VectorXd b_, x_incr_;
- int n_measurements;
- int n_nodes_;
- std::vector<node> nodes_;
- std::vector<measurement> measurements_;
-
- // ordering
- SparseMatrix<int, ColMajor> A_nodes_;
- PermutationMatrix<Dynamic, Dynamic, int> acc_node_permutation_;
-
- CCOLAMDOrdering<int> orderer_;
- VectorXi node_ordering_restrictions_;
- int first_ordered_node_;
-
- // time
- clock_t t_ordering_, t_solving_, t_managing_;
- double time_ordering_, time_solving_, time_managing_;
-
- public:
- SolverQR(const std::string &_name) :
- name_(_name),
- A_(0,0),
- R_(0,0),
-// b_(0),
-// x_(0),
- n_measurements(0),
- n_nodes_(0),
- A_nodes_(0,0),
- acc_node_permutation_(0),
-// nodes_(0),
-// measurements_(0),
- first_ordered_node_(0),
- t_ordering_(0),
- t_solving_(0),
- t_managing_(0),
- time_ordering_(0),
- time_solving_(0),
- time_managing_(0)
- {
- //
- }
-
- virtual ~SolverQR()
- {
-
- }
-
- void add_state_unit(const int node_dim, const int node_idx)
- {
- t_managing_ = clock();
-
- n_nodes_++;
- nodes_.push_back(node(node_idx, node_dim, x_incr_.size(), n_nodes_-1));
-
- // Resize accumulated permutations
- augment_permutation(acc_node_permutation_, n_nodes_);
-
- // Resize state
- x_incr_.conservativeResize(x_incr_.size() + node_dim);
-
- // Resize problem
- A_.conservativeResize(A_.rows(), A_.cols() + node_dim);
- R_.conservativeResize(R_.cols() + node_dim, R_.cols() + node_dim);
- //A_nodes_.conservativeResize(n_measurements, n_nodes); // not necessary
-
- time_managing_ += ((double) clock() - t_managing_) / CLOCKS_PER_SEC;
- }
-
- void addFactor(const measurement& _meas)
- {
- t_managing_ = clock();
-
- assert(_meas.jacobians.size() == _meas.nodes_idx.size());
- assert(_meas.error.size() == _meas.dim);
-
- n_measurements++;
- measurements_.push_back(_meas);
- measurements_.back().location = A_.rows();
-
- // Resize problem
- A_.conservativeResize(A_.rows() + _meas.dim, A_.cols());
- b_.conservativeResize(b_.size() + _meas.dim);
- A_nodes_.conservativeResize(n_measurements,n_nodes_);
-
- // ADD MEASUREMENTS
- first_ordered_node_ = n_nodes_;
- for (unsigned int j = 0; j < _meas.nodes_idx.size(); j++)
- {
- assert(acc_node_permutation_.indices()(_meas.nodes_idx.at(j)) == nodes_.at(_meas.nodes_idx.at(j)).order);
-
- int ordered_node = nodes_.at(_meas.nodes_idx.at(j)).order;//acc_permutation_nodes_.indices()(_nodes_idx.at(j));
-
- addSparseBlock(_meas.jacobians.at(j), A_, A_.rows()-_meas.dim, nodes_.at(_meas.nodes_idx.at(j)).location);
-
- A_nodes_.coeffRef(A_nodes_.rows()-1, ordered_node) = 1;
-
- assert(_meas.jacobians.at(j).cols() == nodes_.at(_meas.nodes_idx.at(j)).dim);
- assert(_meas.jacobians.at(j).rows() == _meas.dim);
-
- // store minimum ordered node
- if (first_ordered_node_ > ordered_node)
- first_ordered_node_ = ordered_node;
- }
-
- // error
- b_.tail(_meas.dim) = _meas.error;
-
- time_managing_ += ((double) clock() - t_managing_) / CLOCKS_PER_SEC;
- }
-
- void ordering(const int & _first_ordered_node)
- {
- t_ordering_ = clock();
-
- // full problem ordering
- if (_first_ordered_node == 0)
- {
- // ordering ordering factors
- node_ordering_restrictions_.resize(n_nodes_);
- node_ordering_restrictions_ = A_nodes_.bottomRows(1).transpose();
-
- // computing nodes partial ordering_
- A_nodes_.makeCompressed();
- PermutationMatrix<Dynamic, Dynamic, int> incr_permutation_nodes(n_nodes_);
- orderer_(A_nodes_, incr_permutation_nodes, node_ordering_restrictions_.data());
-
- // node ordering to variable ordering
- PermutationMatrix<Dynamic, Dynamic, int> incr_permutation(A_.cols());
- nodePermutation2VariablesPermutation(incr_permutation_nodes, incr_permutation);
-
- // apply partial_ordering orderings
- A_nodes_ = (A_nodes_ * incr_permutation_nodes.transpose()).sparseView();
- A_ = (A_ * incr_permutation.transpose()).sparseView();
-
- // ACCUMULATING PERMUTATIONS
- accumulatePermutation(incr_permutation_nodes);
- }
-
- // partial ordering
- else
- {
- int ordered_nodes = n_nodes_ - _first_ordered_node;
- int unordered_nodes = n_nodes_ - ordered_nodes;
- if (ordered_nodes > 2) // only reordering when involved nodes in the measurement are not the two last ones
- {
- // SUBPROBLEM ORDERING (from first node variable to last one)
- //std::cout << "ordering partial_ordering problem: " << _first_ordered_node << " to "<< n_nodes_ - 1 << std::endl;
- SparseMatrix<int> sub_A_nodes_ = A_nodes_.rightCols(ordered_nodes);
-
- // _partial_ordering ordering_ factors
- node_ordering_restrictions_.resize(ordered_nodes);
- node_ordering_restrictions_ = sub_A_nodes_.bottomRows(1).transpose();
-
- // computing nodes partial ordering_
- sub_A_nodes_.makeCompressed();
- PermutationMatrix<Dynamic, Dynamic, int> partial_permutation_nodes(ordered_nodes);
- orderer_(sub_A_nodes_, partial_permutation_nodes, node_ordering_restrictions_.data());
-
- // node ordering to variable ordering
- PermutationMatrix<Dynamic, Dynamic, int> partial_permutation(A_.cols());
- nodePermutation2VariablesPermutation(partial_permutation_nodes, partial_permutation);
-
- // apply partial_ordering orderings
- int ordered_variables = A_.cols() - nodes_.at(_first_ordered_node).location;
- A_nodes_.rightCols(ordered_nodes) = (A_nodes_.rightCols(ordered_nodes) * partial_permutation_nodes.transpose()).sparseView();
- A_.rightCols(ordered_variables) = (A_.rightCols(ordered_variables) * partial_permutation.transpose()).sparseView();
- R_.rightCols(ordered_variables) = (R_.rightCols(ordered_variables) * partial_permutation.transpose()).sparseView();
-
- // ACCUMULATING PERMUTATIONS
- accumulatePermutation(partial_permutation_nodes);
- }
- }
- time_ordering_ += ((double) clock() - t_ordering_) / CLOCKS_PER_SEC;
- }
-
- bool solve(const int mode)
- {
- bool batch = (mode !=2 || first_ordered_node_ == 0);
- bool order = (mode !=0 && n_nodes_ > 1);
-
- // BATCH
- if (batch)
- {
- // REORDER
- if (order)
- ordering(0);
-
- //print_problem();
-
- // SOLVE
- t_solving_ = clock();
- A_.makeCompressed();
- solver_.compute(A_);
- if (solver_.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x_incr_ = solver_.solve(b_);
- R_ = solver_.matrixR();
- //std::cout << "R" << std::endl << MatrixXd::Identity(R_.cols(), R_.cols()) * R_ << std::endl;
- time_solving_ += ((double) clock() - t_solving_) / CLOCKS_PER_SEC;
- }
- // INCREMENTAL
- else
- {
- // REORDER SUBPROBLEM
- ordering(first_ordered_node_);
- //print_problem();
-
- // SOLVE ORDERED SUBPROBLEM
- t_solving_= clock();
- A_nodes_.makeCompressed();
- A_.makeCompressed();
-
- // finding measurements block
- SparseMatrix<int> measurements_to_initial = A_nodes_.col(first_ordered_node_);
- // std::cout << "measurements_to_initial " << measurements_to_initial << std::endl;
- // std::cout << "measurements_to_initial.innerIndex()[measurements_to_initial.outerIndex()[0]] " << measurements_to_initial.innerIndex()[measurements_to_initial.outerIndex()[0]] << std::endl;
- int first_ordered_measurement = measurements_to_initial.innerIndex()[measurements_to_initial.outerIndex()[0]];
- int ordered_measurements = A_.rows() - measurements_.at(first_ordered_measurement).location;
- int ordered_variables = A_.cols() - nodes_.at(first_ordered_node_).location;
- int unordered_variables = nodes_.at(first_ordered_node_).location;
-
- SparseMatrix<double, ColMajor> A_partial = A_.bottomRightCorner(ordered_measurements, ordered_variables);
- solver_.compute(A_partial);
- if (solver_.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- //std::cout << "R new" << std::endl << MatrixXd::Identity(A_partial.cols(), A_partial.cols()) * solver_.matrixR() << std::endl;
- x_incr_.tail(ordered_variables) = solver_.solve(b_.tail(ordered_measurements));
-
- // store new part of R
- eraseSparseBlock(R_, unordered_variables, unordered_variables, ordered_variables, ordered_variables);
- //std::cout << "R" << std::endl << MatrixXd::Identity(R_.rows(), R_.rows()) * R_ << std::endl;
- addSparseBlock(solver_.matrixR(), R_, unordered_variables, unordered_variables);
- //std::cout << "R" << std::endl << MatrixXd::Identity(R_.rows(), R_.rows()) * R_ << std::endl;
- R_.makeCompressed();
-
- // solving not ordered subproblem
- if (unordered_variables > 0)
- {
- //std::cout << "--------------------- solving unordered part" << std::endl;
- SparseMatrix<double, ColMajor> R1 = R_.topLeftCorner(unordered_variables, unordered_variables);
- //std::cout << "R1" << std::endl << MatrixXd::Identity(R1.rows(), R1.rows()) * R1 << std::endl;
- SparseMatrix<double, ColMajor> R2 = R_.topRightCorner(unordered_variables, ordered_variables);
- //std::cout << "R2" << std::endl << MatrixXd::Identity(R2.rows(), R2.rows()) * R2 << std::endl;
- solver_.compute(R1);
- if (solver_.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x_incr_.head(unordered_variables) = solver_.solve(b_.head(unordered_variables) - R2 * x_incr_.tail(ordered_variables));
- }
-
- }
- // UNDO ORDERING FOR RESULT
- PermutationMatrix<Dynamic, Dynamic, int> acc_permutation(A_.cols());
- nodePermutation2VariablesPermutation(acc_node_permutation_, acc_permutation); // TODO via pointers
- x_incr_ = acc_permutation.inverse() * x_incr_;
-
- time_solving_ += ((double) clock() - t_solving_) / CLOCKS_PER_SEC;
-
- return 1;
- }
-
- void nodePermutation2VariablesPermutation(const PermutationMatrix<Dynamic, Dynamic, int> &_perm_nodes, PermutationMatrix<Dynamic, Dynamic, int> &perm_variables)
- {
- ArrayXi locations = perm_nodes_2_locations(_perm_nodes);
-
- int last_idx = 0;
- for (unsigned int i = 0; i<locations.size(); i++)
- {
- perm_variables.indices().segment(last_idx, nodes_.at(i).dim) = VectorXi::LinSpaced(nodes_.at(i).dim, locations(i), locations(i)+nodes_.at(i).dim-1);
- last_idx += nodes_.at(i).dim;
- }
- }
-
- ArrayXi perm_nodes_2_locations(const PermutationMatrix<Dynamic, Dynamic, int> &_perm_nodes)
- {
- ArrayXi indices = _perm_nodes.indices().array();
-
- for (unsigned int i = 0; i<indices.size(); i++)
- indices = (indices > indices(i)).select(indices + nodes_.at(i).dim-1, indices);
-
- return indices;
- }
-
- void augment_permutation(PermutationMatrix<Dynamic, Dynamic, int> &perm, const int new_size)
- {
- int old_size = perm.indices().size();
- int dim = new_size - old_size;
- VectorXi new_indices(new_size);
- new_indices.head(old_size)= perm.indices();
- new_indices.tail(dim) = ArrayXi::LinSpaced(dim, old_size, new_size-1);
- perm.resize(new_size);
- perm.indices() = new_indices;
- }
-
- void accumulatePermutation(const PermutationMatrix<Dynamic, Dynamic, int> &perm)
- {
- printName();
- //std::cout << std::endl << "old acc_permutation_nodes_ " << acc_permutation_nodes_.indices().transpose() << std::endl;
- //std::cout << "incr perm " << perm.indices().transpose() << std::endl;
-
- // acumulate permutation
- if (perm.size() == acc_node_permutation_.size()) //full permutation
- acc_node_permutation_ = perm * acc_node_permutation_;
- else //partial permutation
- {
- PermutationMatrix<Dynamic, Dynamic, int> incr_permutation_nodes(VectorXi::LinSpaced(n_nodes_, 0, n_nodes_ - 1)); // identity permutation
- incr_permutation_nodes.indices().tail(perm.size()) = perm.indices() + VectorXi::Constant(perm.size(), n_nodes_ - perm.size());
- //std::cout << "incr perm " << incr_permutation_nodes.indices().transpose() << std::endl;
- acc_node_permutation_ = incr_permutation_nodes * acc_node_permutation_;
- }
- //std::cout << "new acc_permutation_nodes_ " << acc_permutation_nodes_.indices().transpose() << std::endl;
-
- // update nodes orders and locations
- ArrayXi locations = perm_nodes_2_locations(acc_node_permutation_);
- for (unsigned int i = 0; i < nodes_.size(); i++)
- {
- nodes_.at(i).order = acc_node_permutation_.indices()(i);
- nodes_.at(i).location = locations(i);
- }
- }
-
- void printName()
- {
- std::cout << name_;
- }
-
- void printResults()
- {
- printName();
- std::cout << " solved in " << time_solving_*1e3 << " ms | " << R_.nonZeros() << " nonzeros in R"<< std::endl;
- std::cout << "x = " << x_incr_.transpose() << std::endl;
- }
-
- void printProblem()
- {
- printName();
- std::cout << std::endl << "A_nodes_: " << std::endl << MatrixXi::Identity(A_nodes_.rows(), A_nodes_.rows()) * A_nodes_ << std::endl << std::endl;
- std::cout << "A_: " << std::endl << MatrixXd::Identity(A_.rows(), A_.rows()) * A_ << std::endl << std::endl;
- std::cout << "b_: " << std::endl << b_.transpose() << std::endl << std::endl;
- }
-};
-
-//main
-int main(int argc, char *argv[])
-{
- if (argc != 3 || atoi(argv[1]) < 1|| atoi(argv[2]) < 1)
- {
- std::cout << "Please call me with: [./test_iQR SIZE DIM], where:" << std::endl;
- std::cout << " - SIZE: integer size of the problem" << std::endl;
- std::cout << " - DIM: integer dimension of the nodes" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
- int size = atoi(argv[1]);
- int dim = atoi(argv[2]);
-
- // Problems
- SolverQR solver_ordered("FULL ORDERED");
- SolverQR solver_unordered("UNORDERED");
- SolverQR solver_ordered_partial("PARTIALLY ORDERED");
-
- MatrixXd omega = MatrixXd::Constant(dim, dim, 0.1) + MatrixXd::Identity(dim, dim);
-
- // results variables
- clock_t t_ordering, t_solving_ordered_full, t_solving_unordered, t_solving_ordered_partial, t4;
- double time_ordering=0, time_solving_unordered=0, time_solving_ordered=0, time_solving_ordered_partial=0;
-
- std::cout << "STARTING INCREMENTAL QR TEST" << std::endl << std::endl;
-
- // GENERATING MEASUREMENTS
- std::vector<measurement> measurements;
- for (int i = 0; i < size; i++)
- {
- std::vector<int> meas(0);
- if (i == 0) //prior
- measurements.push_back(measurement(omega, 0, VectorXd::LinSpaced(dim, 0, dim-1), dim));
-
- else //odometry
- measurements.push_back(measurement(2*omega, i-1, 2*omega, i, VectorXd::LinSpaced(dim, dim * i, dim * (i+1)-1), dim, true));
-
- if (i > size / 2) //loop closures
- measurements.push_back(measurement(4*omega, 0, 4*omega, i, VectorXd::LinSpaced(dim, dim * i, dim * (i+1)-1), dim));
- }
-
- // INCREMENTAL LOOP
- for (unsigned int i = 0; i < measurements.size(); i++)
- {
- std::cout << "========================= MEASUREMENT " << i << ":" << std::endl;
-
- // AUGMENT THE PROBLEM ----------------------------
- if (measurements.at(i).odometry_type || i == 0) // if odometry, augment the problem
- {
- solver_unordered.add_state_unit(dim, i);
- solver_ordered.add_state_unit(dim, i);
- solver_ordered_partial.add_state_unit(dim,i);
- }
-
- // ADD MEASUREMENTS
- solver_unordered.addFactor(measurements.at(i));
- solver_ordered.addFactor(measurements.at(i));
- solver_ordered_partial.addFactor(measurements.at(i));
-
- // PRINT PROBLEM
- solver_unordered.printProblem();
- solver_ordered.printProblem();
- solver_ordered_partial.printProblem();
-
- // SOLVING
- solver_unordered.solve(0);
- solver_ordered.solve(1);
- solver_ordered_partial.solve(2);
-
- // RESULTS ------------------------------------
- std::cout << "========================= RESULTS " << i << ":" << std::endl;
- solver_unordered.printResults();
- solver_ordered.printResults();
- solver_ordered_partial.printResults();
-
-// if ((x_ordered_partial-x_ordered).maxCoeff() < 1e-10)
-// std::cout << "Both solutions are equals (tolerance " << (x_ordered_partial-x_ordered).maxCoeff() << ")" << std::endl;
-// else
-// std::cout << "DIFFERENT SOLUTIONS!!!!!!!! max difference " << (x_ordered_partial-x_ordered).maxCoeff() << std::endl;
- }
-}
-
diff --git a/demos/solver/test_iQR_wolf2.cpp b/demos/solver/test_iQR_wolf2.cpp
deleted file mode 100644
index dc4094304..000000000
--- a/demos/solver/test_iQR_wolf2.cpp
+++ /dev/null
@@ -1,430 +0,0 @@
-/*
- * test_iQR_wolf.cpp
- *
- * Created on: Jun 17, 2015
- * Author: jvallve
- */
-
-//std includes
-#include <cstdlib>
-#include <string>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-//Wolf includes
-#include "base/state_block/state_block.h"
-#include "base/factor/factor_base.h"
-#include "base/sensor/sensor_laser_2D.h"
-#include "wolf_manager.h"
-
-// wolf solver
-#include "solver/qr_solver.h"
-
-//C includes for sleep, time and main args
-#include "unistd.h"
-
-//faramotics includes
-#include "faramotics/dynamicSceneRender.h"
-#include "faramotics/rangeScan2D.h"
-#include "btr-headers/pose3d.h"
-
-//Ceres includes
-#include "glog/logging.h"
-#include "base/ceres_wrapper/ceres_manager.h"
-
-//laser_scan_utils
-#include "iri-algorithms/laser_scan_utils/corner_detector.h"
-#include "iri-algorithms/laser_scan_utils/entities.h"
-
-//function travel around
-void motionCampus(unsigned int ii, Cpose3d & pose, double& displacement_, double& rotation_)
-{
- if (ii <= 120)
- {
- displacement_ = 0.1;
- rotation_ = 0;
- }
- else if ((ii > 120) && (ii <= 170))
- {
- displacement_ = 0.2;
- rotation_ = 1.8 * M_PI / 180;
- }
- else if ((ii > 170) && (ii <= 220))
- {
- displacement_ = 0;
- rotation_ = -1.8 * M_PI / 180;
- }
- else if ((ii > 220) && (ii <= 310))
- {
- displacement_ = 0.1;
- rotation_ = 0;
- }
- else if ((ii > 310) && (ii <= 487))
- {
- displacement_ = 0.1;
- rotation_ = -1. * M_PI / 180;
- }
- else if ((ii > 487) && (ii <= 600))
- {
- displacement_ = 0.2;
- rotation_ = 0;
- }
- else if ((ii > 600) && (ii <= 700))
- {
- displacement_ = 0.1;
- rotation_ = -1. * M_PI / 180;
- }
- else if ((ii > 700) && (ii <= 780))
- {
- displacement_ = 0;
- rotation_ = -1. * M_PI / 180;
- }
- else
- {
- displacement_ = 0.3;
- rotation_ = 0.0 * M_PI / 180;
- }
-
- pose.moveForward(displacement_);
- pose.rt.setEuler(pose.rt.head() + rotation_, pose.rt.pitch(), pose.rt.roll());
-}
-
-//main
-int main(int argc, char *argv[])
-{
- using namespace Eigen;
- using namespace wolf;
-
- // USER INPUT ============================================================================================
- if (argc != 3 || atoi(argv[1]) < 1 || atoi(argv[1]) > 1100 || atoi(argv[2]) < 0 || atoi(argv[2]) > 2)
- {
- std::cout << "Please call me with: [./test_ceres_manager NI MODE], where:" << std::endl;
- std::cout << " - NI is the number of iterations (0 < NI < 1100)" << std::endl;
- std::cout << " - MODE is the solver mode (0 batch (no ordering), 1 batch (ordering), 2 incremental" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
- bool complex_angle = false;
- unsigned int solving_mode = (unsigned int) atoi(argv[2]); //solving mode
- unsigned int n_execution = (unsigned int) atoi(argv[1]); //number of iterations of the whole execution
-
- // INITIALIZATION ============================================================================================
-
- //init random generators
- Scalar odom_std_factor = 0.1;
- Scalar gps_std = 10;
- std::default_random_engine generator(1);
- std::normal_distribution<Scalar> gaussian_distribution(0.0, 1);
-
- // Faramotics stuff
- Cpose3d viewPoint, devicePose, laser1Pose, laser2Pose, estimated_vehicle_pose, estimated_laser_1_pose, estimated_laser_2_pose;
- vector < Cpose3d > devicePoses;
- vector<float> scan1, scan2;
- string modelFileName;
-
- //model and initial view point
- modelFileName = "/home/jvallve/iri-lab/faramotics/models/campusNordUPC.obj";
- //modelFileName = "/home/acoromin/dev/br/faramotics/models/campusNordUPC.obj";
- //modelFileName = "/home/andreu/dev/faramotics/models/campusNordUPC.obj";
- devicePose.setPose(2, 8, 0.2, 0, 0, 0);
- viewPoint.setPose(devicePose);
- viewPoint.moveForward(10);
- viewPoint.rt.setEuler(viewPoint.rt.head() + M_PI / 2, viewPoint.rt.pitch() + 30. * M_PI / 180., viewPoint.rt.roll());
- viewPoint.moveForward(-15);
- //glut initialization
- faramotics::initGLUT(argc, argv);
-
- //create a viewer for the 3D model and scan points
- CdynamicSceneRender* myRender = new CdynamicSceneRender(1200, 700, 90 * M_PI / 180, 90 * 700.0 * M_PI / (1200.0 * 180.0), 0.2, 100);
- myRender->loadAssimpModel(modelFileName, true); //with wireframe
- //create scanner and load 3D model
- CrangeScan2D* myScanner = new CrangeScan2D(HOKUYO_UTM30LX_180DEG); //HOKUYO_UTM30LX_180DEG or LEUZE_RS4
- myScanner->loadAssimpModel(modelFileName);
-
- //variables
- Eigen::Vector3s odom_reading;
- Eigen::Vector2s gps_fix_reading;
- Eigen::VectorXs pose_odom(3); //current odometry integred pose
- Eigen::VectorXs ground_truth(n_execution * 3); //all true poses
- Eigen::VectorXs odom_trajectory(n_execution * 3); //open loop trajectory
- Eigen::VectorXs mean_times = Eigen::VectorXs::Zero(7);
- clock_t t1, t2;
-
- // Wolf manager initialization
- Eigen::Vector3s odom_pose = Eigen::Vector3s::Zero();
- Eigen::Vector3s gps_pose = Eigen::Vector3s::Zero();
- Eigen::Vector4s laser_1_pose, laser_2_pose; //xyz + theta
- laser_1_pose << 1.2, 0, 0, 0; //laser 1
- laser_2_pose << -1.2, 0, 0, M_PI; //laser 2
- SensorOdom2D odom_sensor(std::make_shared<StateBlock>(odom_pose.head(2)), std::make_shared<StateBlock>(odom_pose.tail(1)), odom_std_factor, odom_std_factor);
- SensorGPSFix gps_sensor(std::make_shared<StateBlock>(gps_pose.head(2)), std::make_shared<StateBlock>(gps_pose.tail(1)), gps_std);
- SensorLaser2D laser_1_sensor(std::make_shared<StateBlock>(laser_1_pose.head(2)), std::make_shared<StateBlock>(laser_1_pose.tail(1)), laserscanutils::LaserScanParams({M_PI/2,-M_PI/2, -M_PI/720,0.01,0.2,100,0.01,0.01}));
- SensorLaser2D laser_2_sensor(std::make_shared<StateBlock>(laser_2_pose.head(2)), std::make_shared<StateBlock>(laser_2_pose.tail(1)), laserscanutils::LaserScanParams({M_PI/2,-M_PI/2, -M_PI/720,0.01,0.2,100,0.01,0.01}));
-
- // Initial pose
- pose_odom << 2, 8, 0;
- ground_truth.head(3) = pose_odom;
- odom_trajectory.head(3) = pose_odom;
-
- WolfManager* wolf_manager_QR = new WolfManager(FRM_PO_2D, &odom_sensor, pose_odom, Eigen::Matrix3s::Identity() * 0.01, n_execution*10, 0.01);
- WolfManager* wolf_manager_ceres = new WolfManager(FRM_PO_2D, &odom_sensor, pose_odom, Eigen::Matrix3s::Identity() * 0.01, n_execution*10, 0.01);
-
- // Ceres initialization
- ceres::Solver::Options ceres_options;
- ceres_options.minimizer_type = ceres::TRUST_REGION; //ceres::TRUST_REGION;LINE_SEARCH
- ceres_options.max_line_search_step_contraction = 1e-3;
- // ceres_options.minimizer_progress_to_stdout = false;
- // ceres_options.line_search_direction_type = ceres::LBFGS;
- // ceres_options.max_num_iterations = 100;
- CeresManager* ceres_manager = new CeresManager(wolf_manager_ceres->getProblem(), ceres_options);
- std::ofstream log_file, landmark_file; //output file
-
- // Own solver
- SolverQR solver_(wolf_manager_QR->getProblem());
-
- std::cout << "STARTING INCREMENTAL QR TEST" << std::endl << std::endl;
- std::cout << "\n ========= 2D Robot with odometry and 2 LIDARs ===========\n";
- // START TRAJECTORY ============================================================================================
- for (unsigned int step = 1; step < n_execution; step++)
- {
- //get init time
- t2 = clock();
-
- // ROBOT MOVEMENT ---------------------------
- //std::cout << "ROBOT MOVEMENT..." << std::endl;
- // moves the device position
- t1 = clock();
- motionCampus(step, devicePose, odom_reading(0), odom_reading(2));
- odom_reading(1) = 0;
- devicePoses.push_back(devicePose);
-
- // SENSOR DATA ---------------------------
- //std::cout << "SENSOR DATA..." << std::endl;
- // store groundtruth
- ground_truth.segment(step * 3, 3) << devicePose.pt(0), devicePose.pt(1), devicePose.rt.head();
-
- // compute odometry
- odom_reading(0) += gaussian_distribution(generator) * odom_std_factor * (odom_reading(0) == 0 ? 1e-6 : odom_reading(0));
- odom_reading(1) += gaussian_distribution(generator) * odom_std_factor * 1e-6;
- odom_reading(2) += gaussian_distribution(generator) * odom_std_factor * (odom_reading(2) == 0 ? 1e-6 : odom_reading(2));
-
- // odometry integration
- pose_odom(0) = pose_odom(0) + odom_reading(0) * cos(pose_odom(2)) - odom_reading(1) * sin(pose_odom(2));
- pose_odom(1) = pose_odom(1) + odom_reading(0) * sin(pose_odom(2)) + odom_reading(1) * cos(pose_odom(2));
- pose_odom(2) = pose_odom(2) + odom_reading(1);
- odom_trajectory.segment(step * 3, 3) = pose_odom;
-
- // compute GPS
- gps_fix_reading << devicePose.pt(0), devicePose.pt(1);
- gps_fix_reading(0) += gaussian_distribution(generator) * gps_std;
- gps_fix_reading(1) += gaussian_distribution(generator) * gps_std;
-
- //compute scans
- scan1.clear();
- scan2.clear();
- // scan 1
- laser1Pose.setPose(devicePose);
- laser1Pose.moveForward(laser_1_pose(0));
- myScanner->computeScan(laser1Pose, scan1);
- // scan 2
- laser2Pose.setPose(devicePose);
- laser2Pose.moveForward(laser_2_pose(0));
- laser2Pose.rt.setEuler(laser2Pose.rt.head() + M_PI, laser2Pose.rt.pitch(), laser2Pose.rt.roll());
- myScanner->computeScan(laser2Pose, scan2);
-
- mean_times(0) += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // ADD CAPTURES ---------------------------
- //std::cout << "ADD CAPTURES..." << std::endl;
- // adding new sensor captures
- wolf_manager_QR->addCapture(new CaptureOdom2D(TimeStamp(), TimeStamp(), &odom_sensor, odom_reading)); //, odom_std_factor * Eigen::MatrixXs::Identity(2,2)));
- wolf_manager_QR->addCapture(new CaptureGPSFix(TimeStamp(), &gps_sensor, gps_fix_reading, gps_std * gps_std * Eigen::MatrixXs::Identity(3,3)));
- wolf_manager_ceres->addCapture(new CaptureOdom2D(TimeStamp(), TimeStamp(), &odom_sensor, odom_reading)); //, odom_std_factor * Eigen::MatrixXs::Identity(2,2)));
- wolf_manager_ceres->addCapture(new CaptureGPSFix(TimeStamp(), &gps_sensor, gps_fix_reading, gps_std * gps_std * Eigen::MatrixXs::Identity(3,3)));
- //wolf_manager->addCapture(new CaptureLaser2D(TimeStamp(), &laser_1_sensor, scan1));
- //wolf_manager->addCapture(new CaptureLaser2D(TimeStamp(), &laser_2_sensor, scan2));
- // updating problem
- wolf_manager_QR->update();
- wolf_manager_ceres->update();
-
- // UPDATING SOLVER ---------------------------
- //std::cout << "UPDATING..." << std::endl;
- // update state units and factors in ceres
- solver_.update();
-
- // PRINT PROBLEM
- //solver_.printProblem();
-
- // SOLVE OPTIMIZATION ---------------------------
- //std::cout << "SOLVING..." << std::endl;
- ceres::Solver::Summary summary = ceres_manager->solve();
- solver_.solve(solving_mode);
-
- std::cout << "========================= RESULTS " << step << ":" << std::endl;
- //solver_.printResults();
- std::cout << "QR vehicle pose " << wolf_manager_QR->getVehiclePose().transpose() << std::endl;
- std::cout << "ceres vehicle pose " << wolf_manager_ceres->getVehiclePose().transpose() << std::endl;
-
- // COMPUTE COVARIANCES ---------------------------
- //std::cout << "COMPUTING COVARIANCES..." << std::endl;
- // TODO
-
- // DRAWING STUFF ---------------------------
- // draw detected corners
-// std::list < laserscanutils::Corner > corner_list;
-// std::vector<double> corner_vector;
-// CaptureLaser2D last_scan(TimeStamp(), &laser_1_sensor, scan1);
-// last_scan.extractCorners(corner_list);
-// for (std::list<laserscanutils::Corner>::iterator corner_it = corner_list.begin(); corner_it != corner_list.end(); corner_it++)
-// {
-// corner_vector.push_back(corner_it->pt_(0));
-// corner_vector.push_back(corner_it->pt_(1));
-// }
-// myRender->drawCorners(laser1Pose, corner_vector);
-
- // draw landmarks
- std::vector<double> landmark_vector;
- for (auto landmark_it = wolf_manager_QR->getProblem()->getMap()->getLandmarkList().begin(); landmark_it != wolf_manager_QR->getProblem()->getMap()->getLandmarkList().end(); landmark_it++)
- {
- Scalar* position_ptr = (*landmark_it)->getP()->get();
- landmark_vector.push_back(*position_ptr); //x
- landmark_vector.push_back(*(position_ptr + 1)); //y
- landmark_vector.push_back(0.2); //z
- }
- myRender->drawLandmarks(landmark_vector);
-
- // draw localization and sensors
- estimated_vehicle_pose.setPose(wolf_manager_QR->getVehiclePose()(0), wolf_manager_QR->getVehiclePose()(1), 0.2, wolf_manager_QR->getVehiclePose()(2), 0, 0);
- estimated_laser_1_pose.setPose(estimated_vehicle_pose);
- estimated_laser_1_pose.moveForward(laser_1_pose(0));
- estimated_laser_2_pose.setPose(estimated_vehicle_pose);
- // instead of laser 2 we draw ceres solution
- //estimated_laser_2_pose.moveForward(laser_2_pose(0));
- //estimated_laser_2_pose.rt.setEuler(estimated_laser_2_pose.rt.head() + M_PI, estimated_laser_2_pose.rt.pitch(), estimated_laser_2_pose.rt.roll());
- estimated_laser_2_pose.setPose(wolf_manager_ceres->getVehiclePose()(0), wolf_manager_ceres->getVehiclePose()(1), 0.2, wolf_manager_ceres->getVehiclePose()(2), 0, 0);
-
- myRender->drawPoseAxisVector( { estimated_vehicle_pose, estimated_laser_1_pose, estimated_laser_2_pose });
-
- //Set view point and render the scene
- //locate visualization view point, somewhere behind the device
- myRender->setViewPoint(viewPoint);
- myRender->drawPoseAxis(devicePose);
- myRender->drawScan(laser1Pose, scan1, 180. * M_PI / 180., 90. * M_PI / 180.); //draw scan
- myRender->render();
-
- // TIME MANAGEMENT ---------------------------
- double dt = ((double) clock() - t2) / CLOCKS_PER_SEC;
- mean_times(6) += dt;
- if (dt < 0.1)
- usleep(100000 - 1e6 * dt);
-
-// std::cout << "\nTree after step..." << std::endl;
-// wolf_manager->getProblem()->print();
- }
-
- // DISPLAY RESULTS ============================================================================================
- mean_times /= n_execution;
- std::cout << "\nSIMULATION AVERAGE LOOP DURATION [s]" << std::endl;
- std::cout << " data generation: " << mean_times(0) << std::endl;
- std::cout << " wolf managing: " << mean_times(1) << std::endl;
- std::cout << " ceres managing: " << mean_times(2) << std::endl;
- std::cout << " ceres optimization: " << mean_times(3) << std::endl;
- std::cout << " ceres covariance: " << mean_times(4) << std::endl;
- std::cout << " results drawing: " << mean_times(5) << std::endl;
- std::cout << " loop time: " << mean_times(6) << std::endl;
-
-// std::cout << "\nTree before deleting..." << std::endl;
-// wolf_manager->getProblem()->print();
-
- // Draw Final result -------------------------
- std::cout << "Drawing final results..." << std::endl;
- std::vector<double> landmark_vector;
- for (auto landmark_it = wolf_manager_QR->getProblem()->getMap()->getLandmarkList().begin(); landmark_it != wolf_manager_QR->getProblem()->getMap()->getLandmarkList().end(); landmark_it++)
- {
- Scalar* position_ptr = (*landmark_it)->getP()->get();
- landmark_vector.push_back(*position_ptr); //x
- landmark_vector.push_back(*(position_ptr + 1)); //y
- landmark_vector.push_back(0.2); //z
- }
- myRender->drawLandmarks(landmark_vector);
-// viewPoint.setPose(devicePoses.front());
-// viewPoint.moveForward(10);
-// viewPoint.rt.setEuler( viewPoint.rt.head()+M_PI/4, viewPoint.rt.pitch()+20.*M_PI/180., viewPoint.rt.roll() );
-// viewPoint.moveForward(-10);
- myRender->setViewPoint(viewPoint);
- myRender->render();
-
- // Print Final result in a file -------------------------
- std::cout << "Printing results in a file..." << std::endl;
- // Vehicle poses
- std::cout << "Vehicle poses..." << std::endl;
- int i = 0;
- Eigen::VectorXs state_poses(wolf_manager_QR->getProblem()->getTrajectory()->getFrameList().size() * 3);
- for (auto frame_it = wolf_manager_QR->getProblem()->getTrajectory()->getFrameList().begin(); frame_it != wolf_manager_QR->getProblem()->getTrajectory()->getFrameList().end(); frame_it++)
- {
- if (complex_angle)
- state_poses.segment(i, 3) << *(*frame_it)->getP()->get(), *((*frame_it)->getP()->get() + 1), atan2(*(*frame_it)->getO()->get(), *((*frame_it)->getO()->get() + 1));
- else
- state_poses.segment(i, 3) << *(*frame_it)->getP()->get(), *((*frame_it)->getP()->get() + 1), *(*frame_it)->getO()->get();
- i += 3;
- }
-
- // Landmarks
- std::cout << "Landmarks..." << std::endl;
- i = 0;
- Eigen::VectorXs landmarks(wolf_manager_QR->getProblem()->getMap()->getLandmarkList().size() * 2);
- for (auto landmark_it = wolf_manager_QR->getProblem()->getMap()->getLandmarkList().begin(); landmark_it != wolf_manager_QR->getProblem()->getMap()->getLandmarkList().end(); landmark_it++)
- {
- Eigen::Map<Eigen::Vector2s> landmark((*landmark_it)->getP()->get());
- landmarks.segment(i, 2) = landmark;
- i += 2;
- }
-
- // Print log files
- std::string filepath = getenv("HOME") + (complex_angle ? std::string("/Desktop/log_file_3.txt") : std::string("/Desktop/log_file_2.txt"));
- log_file.open(filepath, std::ofstream::out); //open log file
-
- if (log_file.is_open())
- {
- log_file << 0 << std::endl;
- for (unsigned int ii = 0; ii < n_execution; ii++)
- log_file << state_poses.segment(ii * 3, 3).transpose() << "\t" << ground_truth.segment(ii * 3, 3).transpose() << "\t" << (state_poses.segment(ii * 3, 3) - ground_truth.segment(ii * 3, 3)).transpose() << "\t" << odom_trajectory.segment(ii * 3, 3).transpose() << std::endl;
- log_file.close(); //close log file
- std::cout << std::endl << "Result file " << filepath << std::endl;
- }
- else
- std::cout << std::endl << "Failed to write the log file " << filepath << std::endl;
-
- std::string filepath2 = getenv("HOME") + (complex_angle ? std::string("/Desktop/landmarks_file_3.txt") : std::string("/Desktop/landmarks_file_2.txt"));
- landmark_file.open(filepath2, std::ofstream::out); //open log file
-
- if (landmark_file.is_open())
- {
- for (unsigned int ii = 0; ii < landmarks.size(); ii += 2)
- landmark_file << landmarks.segment(ii, 2).transpose() << std::endl;
- landmark_file.close(); //close log file
- std::cout << std::endl << "Landmark file " << filepath << std::endl;
- }
- else
- std::cout << std::endl << "Failed to write the landmark file " << filepath << std::endl;
-
- std::cout << "Press any key for ending... " << std::endl << std::endl;
- std::getchar();
-
- delete myRender;
- delete myScanner;
- delete wolf_manager_QR;
- delete wolf_manager_ceres;
- std::cout << "wolf deleted" << std::endl;
-
- std::cout << " ========= END ===========" << std::endl << std::endl;
-
- //exit
- return 0;
-}
-
diff --git a/demos/solver/test_incremental_ccolamd_blocks.cpp b/demos/solver/test_incremental_ccolamd_blocks.cpp
deleted file mode 100644
index 9283f8411..000000000
--- a/demos/solver/test_incremental_ccolamd_blocks.cpp
+++ /dev/null
@@ -1,262 +0,0 @@
-/*
- * test_ccolamd_blocks.cpp
- *
- * Created on: Jun 12, 2015
- * Author: jvallve
- */
-
-//std includes
-#include <cstdlib>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// eigen includes
-#include <eigen3/Eigen/OrderingMethods>
-#include <eigen3/Eigen/CholmodSupport>
-#include <eigen3/Eigen/SparseLU>
-
-// ccolamd
-#include "solver/ccolamd_ordering.h"
-
-using namespace Eigen;
-
-void eraseSparseBlock(SparseMatrix<double>& original, const unsigned int& row, const unsigned int& Nrows, const unsigned int& col, const unsigned int& Ncols)
-{
- for (unsigned int i = row; i < row + Nrows; i++)
- for (unsigned int j = col; j < row + Ncols; j++)
- original.coeffRef(i,j) = 0.0;
-
- original.makeCompressed();
-}
-
-void addSparseBlock(const MatrixXd& ins, SparseMatrix<double>& original, const unsigned int& row, const unsigned int& col)
-{
- for (unsigned int r=0; r<ins.rows(); ++r)
- for (unsigned int c = 0; c < ins.cols(); c++)
- if (ins(r,c) != 0)
- original.coeffRef(r + row, c + col) += ins(r,c);
-}
-
-void permutation_2_block_permutation(const PermutationMatrix<Dynamic, Dynamic, int> &perm, PermutationMatrix<Dynamic, Dynamic, int> &perm_blocks, const int dim, const int size)
-{
- ArrayXXi idx(dim, size);
- idx.row(0) = dim * perm.indices().transpose();
-
- for (int i = 1; i<dim; i++)
- idx.row(i) = idx.row(i-1) + 1;
- Map<ArrayXi> idx_blocks(idx.data(), dim*size, 1);
- perm_blocks.indices() = idx_blocks;
-}
-
-//main
-int main(int argc, char *argv[])
-{
- if (argc != 3 || atoi(argv[1]) < 1|| atoi(argv[2]) < 1)
- {
- std::cout << "Please call me with: [./test_ccolamd SIZE DIM], where:" << std::endl;
- std::cout << " - SIZE: integer size of the problem" << std::endl;
- std::cout << " - DIM: integer dimension of the nodes" << std::endl;
- std::cout << "EXIT due to bad user input" << std::endl << std::endl;
- return -1;
- }
- int size = atoi(argv[1]);
- int dim = atoi(argv[2]);
-
- // Problem variables
- //CholmodSupernodalLLT < SparseMatrix<double> > solver, solver2, solver3;
- SparseLU < SparseMatrix<double>, NaturalOrdering<int> > solver, solver2, solver3;
- MatrixXd omega = MatrixXd::Constant(dim, dim, 0.1) + MatrixXd::Identity(dim, dim);
- SparseMatrix<double> H(dim,dim),
- H_ordered(dim,dim),
- H_b_ordered(dim,dim);
- VectorXd b(dim),
- b_ordered(dim),
- b_b_ordered(dim),
- x_b_ordered(dim),
- x_ordered(dim),
- x(dim);
-
- // ordering variables
- SparseMatrix<int> factors(1,1), factors_ordered(1,1);
- ArrayXi acc_permutation(dim),
- acc_permutation_b(dim),
- acc_permutation_factors(1);
- acc_permutation = ArrayXi::LinSpaced(dim,0,dim-1);
- acc_permutation_b = acc_permutation;
- acc_permutation_factors(0) = 0;
-
- CCOLAMDOrdering<int> ordering;
- VectorXi factor_ordering_factors(1);
- VectorXi ordering_factors(1);
-
- // results variables
- clock_t t1, t2, t3;
- double time1=0, time2=0, time3=0;
-
- // INITIAL STATE
- addSparseBlock(5*omega, H, 0, 0);
- factors.insert(0,0) = 1;
- b.head(dim) = VectorXd::LinSpaced(Sequential, dim, 0, dim-1);
-
- std::cout << "STARTING INCREMENTAL TEST" << std::endl << std::endl;
-
- // INCREMENTAL LOOP
- for (int i = 1; i < size; i++)
- {
- std::cout << "========================= STEP " << i << ":" << std::endl;
- // AUGMENT THE PROBLEM ----------------------------
- H.conservativeResize((i+1)*dim,(i+1)*dim);
- H_ordered.conservativeResize((i+1)*dim,(i+1)*dim);
- H_b_ordered.conservativeResize((i+1)*dim,(i+1)*dim);
- b.conservativeResize((i+1)*dim);
- b_ordered.conservativeResize((i+1)*dim);
- b_b_ordered.conservativeResize((i+1)*dim);
- x.conservativeResize((i+1)*dim);
- x_ordered.conservativeResize((i+1)*dim);
- x_b_ordered.conservativeResize((i+1)*dim);
- factors.conservativeResize(i+1, i+1);
-
- // Odometry
- addSparseBlock(5*omega, H, i*dim, i*dim);
- addSparseBlock(omega, H, i*dim, (i-1)*dim);
- addSparseBlock(omega, H, (i-1)*dim, i*dim);
- factors.insert(i,i) = 1;
- factors.insert(i,i-1) = 1;
- factors.insert(i-1,i) = 1;
-
- // Loop Closure
- if (i == size-1)
- {
- addSparseBlock(2*omega, H, 0, i*dim);
- addSparseBlock(2*omega, H, i*dim, 0);
- factors.insert(0,i) = 1;
- factors.insert(i,0) = 1;
- }
-
- // r.h.v
- b.segment(i*dim, dim) = VectorXd::LinSpaced(Sequential, dim, dim*i, dim *(i+1)-1);
-
- std::cout << "Solving factor graph:" << std::endl;
- std::cout << "Factors: " << std::endl << factors * MatrixXi::Identity((i+1), (i+1)) << std::endl << std::endl;
-// std::cout << "H: " << std::endl << H * MatrixXd::Identity(dim*(i+1), dim*(i+1)) << std::endl << std::endl;
-
- // SOLVING WITHOUT REORDERING ------------------------------------
- // solve Hx = b
- t1 = clock();
- solver.compute(H);
- if (solver.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x = solver.solve(b);
- time1 += ((double) clock() - t1) / CLOCKS_PER_SEC;
-
- // SOLVING WITH REORDERING ------------------------------------
- // Order with previous orderings
- acc_permutation.conservativeResize(dim*(i+1));
- acc_permutation.tail(dim) = ArrayXi::LinSpaced(dim,dim*i,dim*(i+1)-1);
- PermutationMatrix<Dynamic, Dynamic, int> acc_permutation_matrix(dim*(i+1));
- acc_permutation_matrix.indices() = acc_permutation;
- b_ordered = acc_permutation_matrix * b;
- H_ordered = H.twistedBy(acc_permutation_matrix);
-
- // ordering factors
- ordering_factors.resize(dim*(i+1));
- ordering_factors = ((H_ordered.rightCols(3) * MatrixXd::Ones(3,1)).array() == 0).select(VectorXi::Zero(dim*(i+1)),VectorXi::Ones(dim*(i+1)));
-
- // variable ordering
- t2 = clock();
- H_ordered.makeCompressed();
-
- PermutationMatrix<Dynamic, Dynamic, int> permutation_matrix(dim*(i+1));
- ordering(H_ordered, permutation_matrix, ordering_factors.data());
-
- // applying ordering
- acc_permutation_matrix = permutation_matrix * acc_permutation_matrix;
- acc_permutation = acc_permutation_matrix.indices();
- b_ordered = permutation_matrix * b_ordered;
- H_ordered = H_ordered.twistedBy(permutation_matrix);
-
- // solve Hx = b
- solver2.compute(H_ordered);
- if (solver2.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x_ordered = solver2.solve(b_ordered);
- x_ordered = acc_permutation_matrix.inverse() * x_ordered;
- time2 += ((double) clock() - t2) / CLOCKS_PER_SEC;
-
- // SOLVING WITH BLOCK REORDERING ------------------------------------
- // Order with previous orderings
- acc_permutation_b.conservativeResize(dim*(i+1));
- acc_permutation_b.tail(dim) = ArrayXi::LinSpaced(dim,dim*i,dim*(i+1)-1);
- PermutationMatrix<Dynamic, Dynamic, int> acc_permutation_b_matrix(dim*(i+1));
- acc_permutation_b_matrix.indices() = acc_permutation_b;
- b_b_ordered = acc_permutation_b_matrix * b;
- H_b_ordered = H.twistedBy(acc_permutation_b_matrix);
-
- acc_permutation_factors.conservativeResize(i+1);
- acc_permutation_factors(i) = i;
- PermutationMatrix<Dynamic, Dynamic, int> acc_permutation_factors_matrix(dim*(i+1));
- acc_permutation_factors_matrix.indices() = acc_permutation_factors;
- factors_ordered = factors.twistedBy(acc_permutation_factors_matrix);
-
- // ordering factors
- factor_ordering_factors.resize(i);
- factor_ordering_factors = factors_ordered.rightCols(1);
-
- // block ordering
- t3 = clock();
- factors_ordered.makeCompressed();
-
- PermutationMatrix<Dynamic, Dynamic, int> permutation_factors_matrix(i+1);
- ordering(factors_ordered, permutation_factors_matrix, factor_ordering_factors.data());
-
- // applying ordering
- permutation_2_block_permutation(permutation_factors_matrix, permutation_matrix , dim, i+1);
- acc_permutation_factors_matrix = permutation_factors_matrix * acc_permutation_factors_matrix;
- acc_permutation_factors = acc_permutation_factors_matrix.indices();
- acc_permutation_b_matrix = permutation_matrix * acc_permutation_b_matrix;
- acc_permutation_b = acc_permutation_b_matrix.indices();
- b_b_ordered = permutation_matrix * b_b_ordered;
- H_b_ordered = H_b_ordered.twistedBy(permutation_matrix);
-
- // solve Hx = b
- solver3.compute(H_b_ordered);
- if (solver3.info() != Success)
- {
- std::cout << "decomposition failed" << std::endl;
- return 0;
- }
- x_b_ordered = solver3.solve(b_b_ordered);
- x_b_ordered = acc_permutation_b_matrix.inverse() * x_b_ordered;
- time3 += ((double) clock() - t3) / CLOCKS_PER_SEC;
-
- // RESULTS ------------------------------------
- std::cout << "========================= RESULTS " << i << ":" << std::endl;
- std::cout << "NO REORDERING: solved in " << time1*1e3 << " ms" << std::endl;
- std::cout << "REORDERING: solved in " << time2*1e3 << " ms" << std::endl;
- std::cout << "BLOCK REORDERING: solved in " << time3*1e3 << " ms" << std::endl;
- std::cout << "x1 = " << x.transpose() << std::endl;
- std::cout << "x2 = " << x_ordered.transpose() << std::endl;
- std::cout << "x3 = " << x_b_ordered.transpose() << std::endl;
- }
-
- // RESULTS ------------------------------------
- std::cout << "NO REORDERING: solved in " << time1*1e3 << " ms" << std::endl;
- std::cout << "REORDERING: solved in " << time2*1e3 << " ms" << std::endl;
- std::cout << "BLOCK REORDERING: solved in " << time3*1e3 << " ms" << std::endl;
-
- //std::cout << "x = " << x.transpose() << std::endl;
- //std::cout << "x = " << x_ordered.transpose() << std::endl;
- //std::cout << "x = " << x_b_ordered.transpose() << std::endl;
-}
-
diff --git a/demos/solver/test_permutations.cpp b/demos/solver/test_permutations.cpp
deleted file mode 100644
index c33c744c6..000000000
--- a/demos/solver/test_permutations.cpp
+++ /dev/null
@@ -1,113 +0,0 @@
-/*
- * test_permutations.cpp
- *
- * Created on: Jun 15, 2015
- * Author: jvallve
- */
-
-//std includes
-#include <cstdlib>
-#include <iostream>
-#include <fstream>
-#include <memory>
-#include <random>
-#include <typeinfo>
-#include <ctime>
-#include <queue>
-
-// eigen includes
-#include <eigen3/Eigen/OrderingMethods>
-
-using namespace Eigen;
-
-//main
-int main(int argc, char *argv[])
-{
- PermutationMatrix<Dynamic, Dynamic, int> P1(5), P2(5), P3(5), P4(5);
- P1.setIdentity();
- P2.setIdentity();
- P3.setIdentity();
-
- VectorXd a = VectorXd::LinSpaced(5,1,5);
- MatrixXd A= a.asDiagonal();
- SparseMatrix<double> B = A.sparseView();
- B.makeCompressed();
-
- std::cout << "A (dense)" << std::endl << A << std::endl << std::endl;
- std::cout << "B (sparse)" << std::endl << B << std::endl << std::endl;
-
- P1.indices()(3) = 4;
- P1.indices()(4) = 3;
-
- std::cout << "Permutation 1" << std::endl << P1.indices().transpose() << std::endl << std::endl;
-
- P2.indices()(0) = 4;
- P2.indices()(4) = 0;
-
- std::cout << "Permutation 2" << std::endl << P2.indices().transpose() << std::endl << std::endl;
-
- std::cout << "Pre-multiplying: Permutating rows" << std::endl;
- std::cout << "P1 * A" << std::endl << P1 * A << std::endl << std::endl;
- std::cout << "P1 * B" << std::endl << P1 * B << std::endl << std::endl;
- SparseMatrix<double> C = (P1 * B).sparseView();
- std::cout << "(P1 * B).bottomRows(1)" << std::endl << C.bottomRows(1) << std::endl << std::endl;
-
- std::cout << "Post-multiplying: Permutating cols" << std::endl;
- std::cout << "A * P1.transpose()" << std::endl << A * P1.transpose()<< std::endl << std::endl;
- std::cout << "B * P1.transpose()" << std::endl << B * P1.transpose()<< std::endl << std::endl;
-
- std::cout << "Pre&post-multiplying:" << std::endl;
- std::cout << "P1 * A * P1.transpose()" << std::endl << P1 * A * P1.transpose() << std::endl << std::endl;
- std::cout << "P2 * P1 * A * P1.transpose() * P2.transpose()" << std::endl << P2 * P1 * A * P1.transpose() * P2.transpose() << std::endl << std::endl;
- std::cout << "P1 * P2 * A * P2.transpose() * P1.transpose()" << std::endl << P1 * P2 * A * P2.transpose() * P1.transpose() << std::endl << std::endl;
-
- P3 = P1 * P2;
-
- std::cout << "Permutation P3 = P1 * P2" << std::endl << P3.indices().transpose() << std::endl << std::endl;
- std::cout << "P3 * A * P3.transpose()" << std::endl << P3 * A * P3.transpose() << std::endl << std::endl;
-
- std::cout << "PERMUTATING INDICES" << std::endl;
- ArrayXi acc_permutations(5);
- acc_permutations << 0,1,2,3,4;
-
- std::cout << "acc_permutations: " << acc_permutations.transpose() << std::endl;
-
- std::cout << "P1: " << P1.indices().transpose() << std::endl;
- std::cout << "P1 * acc_permutations: " << (P1 * acc_permutations.matrix()).transpose() << std::endl;
- std::cout << "P1.inverse() * acc_permutations: " << (P1.inverse() * acc_permutations.matrix()).transpose() << std::endl;
-
- std::cout << "P2: " << P2.indices().transpose() << std::endl;
- std::cout << "P2 * (P1 * acc_permutations): " << (P2 * (P1 * acc_permutations.matrix())).transpose() << std::endl;
- std::cout << "(P2 * P1).inverse() * acc_permutations): " << ((P2 * P1).inverse() * acc_permutations.matrix()).transpose() << std::endl;
- P4 = P1 * P2 * P3;
- std::cout << "Permutation P4 = P1 * P2 * P3: " << P4.indices().transpose() << std::endl;
- std::cout << "P3 * (P2 * (P1 * acc_permutations)): " << (P3 * (P2 * (P1 * acc_permutations.matrix()))).transpose() << std::endl;
- std::cout << "accumulated permutations can not be stored in vectors..." << std::endl;
-
- std::cout << std::endl << "PARTIALL PERMUTATIONS" << std::endl;
- PermutationMatrix<Dynamic, Dynamic, int> P5(2);
- P5.indices()(0) = 1;
- P5.indices()(1) = 0;
- std::cout << "P5 (equivalent to P1 but partiall): " << std::endl << P5.indices().transpose() << std::endl;
- std::cout << "P2: " << P2.indices().transpose() << std::endl << std::endl;
- std::cout << "A * P2.transpose(): " << std::endl << A * P2.transpose() << std::endl << std::endl;
- std::cout << "(A * P2.transpose()).rightCols(2) * P5.transpose(): " << std::endl << (A * P2.transpose()).rightCols(2) * P5.transpose() << std::endl << std::endl;
- PermutationMatrix<Dynamic, Dynamic, int> P6 = P2;
- P6.indices().tail(2) = P5 * P6.indices().tail(2);
- std::cout << "P6 = P2, P6.indices().tail(2) = P5 * P6.indices().tail(2): " << P6.indices().transpose() << std::endl << std::endl;
- std::cout << "A * P6.transpose(): " << std::endl << A * P6.transpose() << std::endl << std::endl;
- std::cout << "(P1 * P2): " << std::endl << (P1 * P2).indices().transpose() << std::endl << std::endl;
- std::cout << "A * (P1 * P2).transpose(): " << std::endl << A * (P1 * P2).transpose() << std::endl << std::endl;
- std::cout << "Partiall permutations can not be accumulated, for doing that they should be full size" << std::endl;
-
- std::cout << std::endl << "PERMUTATION OF MAPPED VECTORS" << std::endl;
- std::cout << "a = " << a.transpose() << std::endl << std::endl;
- Map<VectorXd> mapped_a(a.data(), 1);
- std::cout << "mapped_a1 = " << mapped_a << std::endl << std::endl;
- a = P2 * a;
- std::cout << "a = P2 * a: " << std::endl << a.transpose() << std::endl << std::endl;
- std::cout << "mapped_a = " << mapped_a.transpose() << std::endl << std::endl;
- std::cout << "maps are affected of the reorderings in mapped vectors" << std::endl;
-
-// Map<>
-}
--
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