demos/map_apriltag_1.yaml

-map name: "Example of map of Apriltag landmarks"
-
-nlandmarks: 4          # This must match the number of landmarks in the list that follows. Otherwise it is an error.
-
-landmarks:
-
-  - 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: 0.1
-    position: [0, 0, 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: 0.1
-    position: [1, 1, 0]
-    orientation: [0, 0, 0]    # roll pitch yaw in degrees
-    position fixed: true
-    orientation fixed: true
-
-  - id : 5                    # use same as tag id
-    type: "APRILTAG"          # This must match the KEY used in the LandmarkFactory. Otherwise it is an error.
-    tag id: 5
-    tag width: 0.1
-    position: [1, 0, 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: 0.1
-    position: [0, 1, 0]
-    orientation: [0, 0, 0]    # roll pitch yaw in degrees
-    position fixed: true
-    orientation fixed: true
-

demos/map_polyline_example.yaml

-map name: "Example of map of Polyline2D landmarks"
-
-nlandmarks: 4          # This must match the number of landmarks in the list that follows. Otherwise it is an error.
-
-landmarks:
-
-  - id: 1
-    type: "POLYLINE 2D"   # This must match the KEY used in the LandmarkFactory. Otherwise it is an error.
-    position: [1, 1]
-    orientation: [1]
-    position fixed: true
-    orientation fixed: true
-    classification: 0
-    first_id: 0
-    first_defined: false
-    last_defined: false
-    points:
-        - [1, 1]
-        - [1, 2]
-        - [1, 3]
-
-  - id: 4
-    type: "POLYLINE 2D"   # This must match the KEY used in the LandmarkFactory. Otherwise it is an error.
-    position: [4, 4]
-    orientation: [4]
-    position fixed: true
-    orientation fixed: true
-    classification: 0
-    first_id: -2
-    first_defined: false
-    last_defined: true
-    points:
-        - [4, 1]
-        - [4, 2]
-        - [4, 3]
-        - [4, 4]
-
-        
-  - id: 6
-    type: "POLYLINE 2D"   # This must match the KEY used in the LandmarkFactory. Otherwise it is an error.
-    position: [6, 6]
-    orientation: [6]
-    position fixed: true
-    orientation fixed: true
-    classification: 0
-    first_id: 0
-    first_defined: true
-    last_defined: false
-    points:
-        - [6, 1]
-        - [6, 2]
-        
-  - id: 7
-    type: "AHP"
-    position: [1, 2, 3, 4]
-    descriptor: [1, 0, 1, 0, 1, 1, 0, 0]
-        
\ No newline at end of file

demos/maps/map_apriltag_logitech_1234.yaml

-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
-

demos/processor_image_feature.yaml

-processor type: "IMAGE ORB"
-processor name: "ORB feature tracker"
-
-vision_utils:
-    YAML file params: processor_image_vision_utils.yaml
-
-algorithm:
-    maximum new features: 40
-    minimum features for new keyframe: 40
-    minimum response for new features: 80 #0.0005
-    time tolerance: 0.01
-    distance: 20
-    
-noise:
-    pixel noise std: 1 # pixels
-    
-draw: # Used to control drawing options
-    primary draw: true
-    secondary draw: true
-    detection roi: true
-    tracking roi: false
-    

demos/processor_image_vision_utils.yaml

-sensor:
-  type: "USB_CAM"
-
-detector:
-  type: "ORB"         
-  nfeatures: 100
-  scale factor: 1.2
-  nlevels: 8
-  edge threshold: 8   # 16
-  first level: 0 
-  WTA_K: 2            # See: http://docs.opencv.org/trunk/db/d95/classcv_1_1ORB.html#a180ae17d3300cf2c619aa240d9b607e5
-  score type: 1       #enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };
-  patch size: 15      # 31
-
-descriptor:
-  type: "ORB"         
-  nfeatures: 100
-  scale factor: 1.2
-  nlevels: 8
-  edge threshold: 8   # 16
-  first level: 0 
-  WTA_K: 2            # See: http://docs.opencv.org/trunk/db/d95/classcv_1_1ORB.html#a180ae17d3300cf2c619aa240d9b607e5
-  score type: 1       #enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };
-  patch size: 15      # 31
-
-matcher:
-  type: "FLANNBASED"
-  match type: 1     #  Match type. MATCH = 1, KNNMATCH = 2, RADIUSMATCH = 3
-  roi:
-    width: 20
-    height: 20
-  min normalized score: 0.85 
-    
-algorithm:
-  type: "ACTIVESEARCH"   
-  draw results: false
-  grid horiz cells: 12
-  grid vert cells: 8
-  separation: 10
-  min features to track: 5
-  max new features: 40
-  min response new features: 80
\ No newline at end of file

demos/processor_imu.yaml

-processor type: "IMU"              # This must match the KEY used in the SensorFactory. Otherwise it is an error.
-processor name: "Main imu"        # This is ignored. The name provided to the SensorFactory prevails
-unmeasured perturbation std: 0.00001
-time tolerance: 0.0025         # Time tolerance for joining KFs
-keyframe vote:
-    max time span:      2.0   # seconds
-    max buffer length:  20000    # motion deltas
-    dist traveled:      2.0   # meters
-    angle turned:       0.2   # radians (1 rad approx 57 deg, approx 60 deg)
-    voting_active:      false
-    
\ No newline at end of file

demos/processor_imu_no_vote.yaml

-processor type: "IMU"              # This must match the KEY used in the SensorFactory. Otherwise it is an error.
-processor name: "Main imu"        # This is ignored. The name provided to the SensorFactory prevails
-time tolerance: 0.0025         # Time tolerance for joining KFs
-unmeasured perturbation std: 0.00001
-keyframe vote:
-    max time span:      999999.0   # seconds
-    max buffer length:  999999     # motion deltas
-    dist traveled:      999999.0   # meters
-    angle turned:       999999     # radians (1 rad approx 57 deg, approx 60 deg)
-    voting_active:      false
-    
\ No newline at end of file

demos/processor_imu_t1.yaml

-processor type: "IMU"              # This must match the KEY used in the SensorFactory. Otherwise it is an error.
-processor name: "Main imu"        # This is ignored. The name provided to the SensorFactory prevails
-unmeasured perturbation std: 0.00001
-time tolerance: 0.0025         # Time tolerance for joining KFs
-keyframe vote:
-    max time span:      0.9999   # seconds
-    max buffer length:  10000    # motion deltas
-    dist traveled:      10000   # meters
-    angle turned:       10000   # radians (1 rad approx 57 deg, approx 60 deg)
-    voting_active:      true
-    
\ No newline at end of file

demos/processor_imu_t6.yaml

-processor type: "IMU"              # This must match the KEY used in the SensorFactory. Otherwise it is an error.
-processor name: "Main imu"        # This is ignored. The name provided to the SensorFactory prevails
-unmeasured perturbation std: 0.00001
-time tolerance: 0.0025         # Time tolerance for joining KFs
-keyframe vote:
-    max time span:      5.9999   # seconds
-    max buffer length:  10000    # motion deltas
-    dist traveled:      10000   # meters
-    angle turned:       10000   # radians (1 rad approx 57 deg, approx 60 deg)
-    voting_active:      true
-    
\ No newline at end of file

demos/processor_odom_3D.yaml

-processor type: "ODOM 3D"              # This must match the KEY used in the SensorFactory. Otherwise it is an error.
-processor name: "Main odometer"        # This is ignored. The name provided to the SensorFactory prevails
-time tolerance:         0.01  # seconds
-keyframe vote:
-    max time span:      0.2   # seconds
-    max buffer length:  10    # motion deltas
-    dist traveled:      0.5   # meters
-    angle turned:       0.1   # radians (1 rad approx 57 deg, approx 60 deg)
\ No newline at end of file
+type: "ODOM 3D"              # This must match the KEY used in the SensorFactory. Otherwise it is an error.
+
+time_tolerance:         0.01  # seconds
+unmeasured_perturbation_std: 0.001
+
+keyframe_vote:
+  voting_active:          false
+  voting_aux_active:      false
+  max_time_span:          0.2   # seconds
+  max_buff_length:        10    # motion deltas
+  dist_traveled:          0.5   # meters
+  angle_turned:           0.1   # radians (1 rad approx 57 deg, approx 60 deg)
+

demos/processor_tracker_feature_trifocal.yaml

-processor type: "TRACKER FEATURE TRIFOCAL"
-processor name: "tracker feature trifocal example"
-
-vision_utils:
-    YAML file params: ACTIVESEARCH.yaml
-
-algorithm:
-    time tolerance: 0.01
-    voting active: true
-    minimum features for keyframe: 40
-    maximum new features: 40
-    grid horiz cells: 10
-    grid vert cells: 10
-    min response new features: 50   
-    max euclidean distance: 20 
-    
-noise:
-    pixel noise std: 1 # pixels
-    

demos/processor_tracker_landmark_apriltag.yaml

-processor type: "TRACKER LANDMARK APRILTAG"
-processor name: "tracker landmark apriltag example"
-
-detector parameters: 
-    quad_decimate:  1.5      # doing quad detection at lower resolution to speed things up (see end of file)
-    quad_sigma:     0.8	     # gaussian blur good for noisy images, may be recommended with quad_decimate. Kernel size adapted (see end of this file) 
-    nthreads:       8       # how many thread during tag detection (does not change much?)
-    debug:          false    # write some debugging images
-    refine_edges:   true    # better edge detection if quad_decimate > 1 (quite inexpensive, almost no diff)
-    ippe_min_ratio:     3.0  	# quite arbitrary, always > 1 (to deactive, set at 0 for example)
-    ippe_max_rep_error: 2.0     # to deactivate, set at something big (100)
-
-tag widths:                    
-    0: 0.055
-    1: 0.055
-    2: 0.055
-    3: 0.055
-
-tag parameters:
-    tag_family:           "tag36h11" 
-    # tag_black_border:     1
-    tag_width_default:    0.165   # used if tag width not specified
-
-    
-noise:
-    std_xy :          0.1 # m 
-    std_z :           0.1 # m 
-    std_rpy_degrees : 5   # degrees
-    std_pix:          20    # pixel error
-    
-vote:
-    voting active:              true
-    min_time_vote:              0 # s
-    max_time_vote:              0 # s
-    min_features_for_keyframe:  12
-    max_features_diff:          17
-    nb_vote_for_every_first:    50
-    enough_info_necessary:      true   # create kf if enough information to uniquely determine the KF position (necessary for apriltag_only slam)
-
-reestimate_last_frame: true   # for a better prior on the new keyframe: use only if no motion processor
-add_3D_cstr: true             # add 3D constraints between the KF so that they do not jump when using apriltag only
-
-
-# Annexes:
-### Quad decimate: the higher, the lower the resolution
-# Does nothing if <= 1.0
-# Only values taken into account:
-# 1.5, 2, 3, 4
-# 1.5 -> ~*2 speed up
-
-# Higher values use a "bad" code according to commentaries in the library, smaller do nothing
-### Gaussian blur table:
-# max sigma          kernel size
-# 0.499              1  (disabled)
-# 0.999              3
-# 1.499              5
-# 1.999              7

demos/sensor_imu.yaml

-sensor type: "IMU"             # This must match the KEY used in the SensorFactory. Otherwise it is an error.
-sensor name: "Main IMU"        # This is ignored. The name provided to the SensorFactory prevails
-motion variances: 
-    a_noise:                0.053     # standard deviation of Acceleration noise (same for all the axis) in m/s2
-    w_noise:                0.0011    # standard deviation of Gyroscope noise (same for all the axis) in rad/sec
-    ab_initial_stdev:       0.800     # m/s2    - initial bias 
-    wb_initial_stdev:       0.350     # rad/sec - initial bias 
-    ab_rate_stdev:          0.1       # m/s2/sqrt(s)           
-    wb_rate_stdev:          0.0400    # rad/s/sqrt(s)
\ No newline at end of file

demos/sensor_odom_3D.yaml

-sensor type: "ODOM 3D"              # This must match the KEY used in the SensorFactory. Otherwise it is an error.
-sensor name: "Main odometer"        # This is ignored. The name provided to the SensorFactory prevails
-motion variances: 
-    disp_to_disp:   0.02  # m^2   / m
-    disp_to_rot:    0.02  # rad^2 / m
-    rot_to_rot:     0.01  # rad^2 / rad
-    min_disp_var:   0.01  # m^2
-    min_rot_var:    0.01  # rad^2
+type: "ODOM 3D"              # This must match the KEY used in the SensorFactory. Otherwise it is an error.
+
+k_disp_to_disp:   0.02  # m^2   / m
+k_disp_to_rot:    0.02  # rad^2 / m
+k_rot_to_rot:     0.01  # rad^2 / rad
+min_disp_var:     0.01  # m^2
+min_rot_var:      0.01  # rad^2

demos/sensor_odom_3D_HQ.yaml

-sensor type: "ODOM 3D"              # This must match the KEY used in the SensorFactory. Otherwise it is an error.
-sensor name: "Main odometer"        # This is ignored. The name provided to the SensorFactory prevails
-motion variances: 
-    disp_to_disp:   0.000001  # m^2   / m
-    disp_to_rot:    0.000001  # rad^2 / m
-    rot_to_rot:     0.000001  # rad^2 / rad
-    min_disp_var:   0.00000001  # m^2
-    min_rot_var:    0.00000001  # rad^2
\ No newline at end of file
+type: "ODOM 3D"              # This must match the KEY used in the SensorFactory. Otherwise it is an error.
+
+k_disp_to_disp:   0.000001  # m^2   / m
+k_disp_to_rot:    0.000001  # rad^2 / m
+k_rot_to_rot:     0.000001  # rad^2 / rad
+min_disp_var:     0.00000001  # m^2
+min_rot_var:      0.00000001  # rad^2
\ No newline at end of file

demos/vision_utils_active_search.yaml

-sensor:
-  type: "USB_CAM"
-
-detector:
-  type: "ORB"         
-  nfeatures: 100
-  scale factor: 1.2
-  nlevels: 8
-  edge threshold: 8   # 16
-  first level: 0 
-  WTA_K: 2            # See: http://docs.opencv.org/trunk/db/d95/classcv_1_1ORB.html#a180ae17d3300cf2c619aa240d9b607e5
-  score type: 1       #enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };
-  patch size: 15      # 31
-
-descriptor:
-  type: "ORB"         
-  nfeatures: 100
-  scale factor: 1.2
-  nlevels: 8
-  edge threshold: 8   # 16
-  first level: 0 
-  WTA_K: 2            # See: http://docs.opencv.org/trunk/db/d95/classcv_1_1ORB.html#a180ae17d3300cf2c619aa240d9b607e5
-  score type: 1       #enum { kBytes = 32, HARRIS_SCORE=0, FAST_SCORE=1 };
-  patch size: 15      # 31
-
-matcher:
-  type: "FLANNBASED"
-  match type: 1     #  Match type. MATCH = 1, KNNMATCH = 2, RADIUSMATCH = 3
-  roi:
-    width: 20
-    height: 20
-  min normalized score: 0.85 
-    
-algorithm:
-  type: "ACTIVESEARCH"   
-  draw results: true
-  grid horiz cells: 12
-  grid vert cells: 8
-  separation: 10
-  min features to track: 5
-  max new features: 40
-  min response new features: 80
\ No newline at end of file

hello_wolf/hello_wolf.cpp

@@ -139,12 +139,12 @@ int main()
 
     // SELF CALIBRATION ===================================================
 
-    // NOTE: SELF-CALIBRATION OF SENSOR ORIENTATION
+    // SELF-CALIBRATION OF SENSOR ORIENTATION
     // Uncomment this line below to achieve sensor self-calibration (of the orientation only, since the position is not observable)
-    sensor_rb->getO()->unfix();
+    // sensor_rb->getO()->unfix();
 
-    // NOTE: SELF-CALIBRATION OF SENSOR POSITION
-    // The position is however not observable, and thus self-calibration would not work. You can try uncommenting it too.
+    // SELF-CALIBRATION OF SENSOR POSITION
+    // The position is however not observable, and thus self-calibration would not work. You can try uncommenting the line below.
     // sensor_rb->getP()->unfix();
 
     // CONFIGURE ==========================================================

hello_wolf/hello_wolf_autoconf.cpp

@@ -101,13 +101,14 @@ int main()
     using namespace wolf;
 
 
-    WOLF_TRACE("======== CONFIGURE PROBLEM =======")
+    WOLF_TRACE("======== CONFIGURE PROBLEM =======");
 
     // Config file to parse. Here is where all the problem is defined:
-    std::string file = std::string(_WOLF_ROOT_DIR) + "/hello_wolf/hello_wolf_config.yaml";
+    std::string config_file = "hello_wolf/yaml/hello_wolf_config.yaml";
+    std::string wolf_path   = std::string(_WOLF_ROOT_DIR);
 
     // parse file into params server: each param will be retrievable from this params server:
-    ParserYAML parser = ParserYAML(file);
+    ParserYAML parser = ParserYAML(config_file, wolf_path);
     parser.parse();
     ParamsServer server = ParamsServer(parser.getParams(), parser.sensorsSerialization(), parser.processorsSerialization());
 
@@ -118,8 +119,8 @@ int main()
     problem->print(4,0,1,0);
 
     // recover sensor pointers for later use (access by sensor name)
-    SensorBasePtr sensor_odo    = problem->getSensor("odom");
-    SensorBasePtr sensor_rb     = problem->getSensor("rb");
+    SensorBasePtr sensor_odo    = problem->getSensor("sen odom");
+    SensorBasePtr sensor_rb     = problem->getSensor("sen rb");
 
     // Solver. Configure a Ceres solver
     ceres::Solver::Options options;
@@ -131,12 +132,12 @@ int main()
     // SELF CALIBRATION ===================================================
     // These few lines control whether we calibrate some sensor parameters or not.
 
-    // NOTE: SELF-CALIBRATION OF SENSOR ORIENTATION
+    // SELF-CALIBRATION OF SENSOR ORIENTATION
     // Uncomment this line below to achieve sensor self-calibration (of the orientation only, since the position is not observable)
-    sensor_rb->getO()->unfix();
+    // sensor_rb->getO()->unfix();
 
-    // NOTE: SELF-CALIBRATION OF SENSOR POSITION
-    // The position is however not observable, and thus self-calibration would not work. You can try uncommenting it too.
+    // SELF-CALIBRATION OF SENSOR POSITION
+    // The position is however not observable, and thus self-calibration would not work. You can try uncommenting the line below.
     // sensor_rb->getP()->unfix();
 
     // CONFIGURE input data (motion and measurements) ==============================================
@@ -151,7 +152,7 @@ int main()
 
     // SET OF EVENTS: make things happen =======================================================
     std::cout << std::endl;
-    WOLF_TRACE("======== BUILD PROBLEM =======")
+    WOLF_TRACE("======== START ROBOT MOVE AND SLAM =======")
 
     // We'll do 3 steps of motion and landmark observations.
 

hello_wolf/hello_wolf_config.yaml

-config:
-
-  problem:
-    frame structure:      "PO"
-    dimension:            2
-    prior timestamp:      0.0
-    prior state:          [0,0,0]
-    prior cov:            [[3,3],.01,0,0,0,.01,0,0,0,.01]
-    prior time tolerance: 0.1
-    
- 
-  sensors:
-    -
-      type: "ODOM 2D"
-      name: "odom"
-
-    - 
-      type:                       "RANGE BEARING"
-      name:                       "rb"  
-      noise range metres std:     0.1
-      noise bearing degrees std:  0.5  
-      
-  processors:
-    -
-      type:           "ODOM 2D"
-      name:           "odom"
-      sensor name:    "odom"
-      voting active:  true
-      time tolerance: 0.1
-      max time span:  999
-      dist_traveled:  0.95
-      angle_turned:   999
-      cov_det:        999
-      unmeasured_perturbation_std: 0.001
-    
-    -
-      type:         "RANGE BEARING"
-      name:         "rb"
-      sensor name:  "rb"
-    
-    
-files:
-#    - "/Users/jsola/dev/wolf_lib/core/lib/libhellowolf.dylib"
-  
-    
\ No newline at end of file

hello_wolf/processor_range_bearing.cpp

@@ -14,10 +14,10 @@
 namespace wolf
 {
 
-ProcessorRangeBearing::ProcessorRangeBearing(const SensorRangeBearingPtr _sensor_ptr, ProcessorParamsBasePtr _params) :
+ProcessorRangeBearing::ProcessorRangeBearing(ProcessorParamsBasePtr _params) :
         ProcessorBase("RANGE BEARING", _params)
 {
-    H_r_s   = transform(_sensor_ptr->getP()->getState(), _sensor_ptr->getO()->getState());
+    //
 }
 
 void ProcessorRangeBearing::processCapture(CaptureBasePtr _capture)
@@ -75,7 +75,7 @@ void ProcessorRangeBearing::processCapture(CaptureBasePtr _capture)
         {
             // new landmark:
             // - create landmark
-            lmk = std::static_pointer_cast<LandmarkPoint2D>(LandmarkBase::emplace<LandmarkPoint2D>(getProblem()->getMap(), id, invObserve(range, bearing)));
+            lmk = LandmarkBase::emplace<LandmarkPoint2D>(getProblem()->getMap(), id, invObserve(range, bearing));
             WOLF_TRACE("new   lmk(", id, "): ", lmk->getP()->getState().transpose());
             // - add to known landmarks
             known_lmks.emplace(id, lmk);
@@ -99,39 +99,6 @@ void ProcessorRangeBearing::processCapture(CaptureBasePtr _capture)
 
 }
 
-ProcessorBasePtr ProcessorRangeBearing::create(const std::string& _unique_name,
-                                               const ProcessorParamsBasePtr _params,
-                                               const SensorBasePtr _sen_ptr)
-{
-    SensorRangeBearingPtr       sensor_rb = std::static_pointer_cast<SensorRangeBearing>(_sen_ptr);
-    ProcessorParamsRangeBearingPtr params = std::static_pointer_cast<ProcessorParamsRangeBearing>(_params);
-
-    // construct processor
-    ProcessorRangeBearingPtr prc = std::make_shared<ProcessorRangeBearing>(sensor_rb, params);
-
-    // setup processor
-    prc->setName(_unique_name);
-
-    return prc;
-}
-
-ProcessorBasePtr ProcessorRangeBearing::createAutoConf(const std::string& _unique_name,
-                                                       const ParamsServer& _server,
-                                                       const SensorBasePtr _sensor_ptr)
-{
-    SensorRangeBearingPtr       sensor_rb = std::static_pointer_cast<SensorRangeBearing>(_sensor_ptr);
-    ProcessorParamsRangeBearingPtr params = std::make_shared<ProcessorParamsRangeBearing>();
-    params->voting_active = _server.getParam<bool>(_unique_name + "/voting_active", "false");
-    params->time_tolerance = _server.getParam<double>(_unique_name + "/time_tolerance", "0.01");
-
-    // construct processor
-    ProcessorRangeBearingPtr prc = std::make_shared<ProcessorRangeBearing>(sensor_rb, params);
-
-    // setup processor
-    prc->setName(_unique_name);
-
-    return prc;
-}
 
 Eigen::Vector2s ProcessorRangeBearing::observe(const Eigen::Vector2s& lmk_w) const
 {
@@ -189,10 +156,6 @@ Eigen::Vector2s ProcessorRangeBearing::rect(Scalar range, Scalar bearing) const
 namespace wolf
 {
 WOLF_REGISTER_PROCESSOR("RANGE BEARING", ProcessorRangeBearing)
-} // namespace wolf
-#include "core/processor/autoconf_processor_factory.h"
-namespace wolf
-{
 WOLF_REGISTER_PROCESSOR_AUTO("RANGE BEARING", ProcessorRangeBearing)
 } // namespace wolf