From aaab84f364caab9a713a73e699d283f22688b23d Mon Sep 17 00:00:00 2001
From: Idril Geer <igeer@iri.upc.edu>
Date: Wed, 9 Feb 2022 21:08:34 +0100
Subject: [PATCH] added matlab analysys scripts
---
bag/.gitignore | 6 +-
bag/analysys/ang10.jpg | Bin 0 -> 53983 bytes
bag/analysys/compare.asv | 44 +
bag/analysys/compare.m | 45 +
bag/analysys/dist10.jpg | Bin 0 -> 48089 bytes
bag/analysys/extractGT.asv | 39 +
bag/analysys/extractGT.m | 45 +
bag/analysys/extractdata.m | 32 +
bag/analysys/groundtruth_trajectory_lab2.csv | 4034 ++++++++++++++++++
bag/analysys/interparc.m | 574 +++
bag/analysys/matchaxes.asv | 24 +
bag/analysys/matchaxes.m | 22 +
bag/analysys/ploterrs.m | 26 +
bag/generate_trajectory_csv.bash | 9 +-
bag/transpose_csv.py | 2 +-
yaml/trajectory_analysys/E-1_0.yaml | 4 +-
yaml/trajectory_analysys/G-1_0.yaml | 2 +-
yaml/trajectory_analysys/hold/E-0_1.yaml | 157 +
yaml/trajectory_analysys/hold/G-0_1.yaml | 115 +
19 files changed, 5171 insertions(+), 9 deletions(-)
create mode 100644 bag/analysys/ang10.jpg
create mode 100644 bag/analysys/compare.asv
create mode 100644 bag/analysys/compare.m
create mode 100644 bag/analysys/dist10.jpg
create mode 100644 bag/analysys/extractGT.asv
create mode 100644 bag/analysys/extractGT.m
create mode 100644 bag/analysys/extractdata.m
create mode 100644 bag/analysys/groundtruth_trajectory_lab2.csv
create mode 100644 bag/analysys/interparc.m
create mode 100644 bag/analysys/matchaxes.asv
create mode 100644 bag/analysys/matchaxes.m
create mode 100644 bag/analysys/ploterrs.m
create mode 100644 yaml/trajectory_analysys/hold/E-0_1.yaml
create mode 100644 yaml/trajectory_analysys/hold/G-0_1.yaml
diff --git a/bag/.gitignore b/bag/.gitignore
index f960d91..b31508b 100644
--- a/bag/.gitignore
+++ b/bag/.gitignore
@@ -1,5 +1,7 @@
-*
-*/
+*.bag
+CSV/
+recordings/
+!analysys/
!.gittignore
!*.bash
!*.py
diff --git a/bag/analysys/ang10.jpg b/bag/analysys/ang10.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..a09435389ff57b74c7bb5c040a70b9b83625ac21
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diff --git a/bag/analysys/compare.asv b/bag/analysys/compare.asv
new file mode 100644
index 0000000..0f21731
--- /dev/null
+++ b/bag/analysys/compare.asv
@@ -0,0 +1,44 @@
+clc; clear; clearvars; close all;
+
+CSVFolder = '../CSV/transp/';
+if ~isfolder(CSVFolder)
+ errorMessage = sprintf('Error: The following folder does not exist:\n%s\nPlease specify a new folder.', myFolder);
+ uiwait(warndlg(errorMessage));
+ myFolder = uigetdir(); % Ask for a new one.
+ if myFolder == 0
+ % User clicked Cancel
+ return;
+ end
+end
+Gvec = [];
+Evec = [];
+myFiles = dir(fullfile(CSVFolder,'*.csv')); %gets all csv files in struct
+for k = 1:length(myFiles)
+ baseFileName = myFiles(k).name;
+ fullFileName = fullfile(CSVFolder, baseFileName);
+ fprintf('Now reading file %s\n', baseFileName);
+ Table = readtable(fullFileName,'PreserveVariableNames',true);
+ if baseFileName(1) == 'G'
+ [Gx, Gy, Gz, Gang, Gt, Gts] = extractGT(Table);
+ Gvec = [Gvec, {baseFileName, Gx, Gy, Gz, Gang, Gt, Gts}'];
+ elseif baseFileName(1) == 'E'
+ [Ex, Ey, Ez, Eang, Et, Ets] = extractdata(Table);
+ Evec = [Evec, {baseFileName, Ex, Ey, Ez, Eang, Et, Ets}'];
+ end
+
+%
+% t10 = linspace(0,min(Gt(end),gt10(end))-1,1e6);
+% ts0 = resample(Gts, t10);
+% ts1 = resample(gts10, t10);
+% ploterrs(ts0, ts1)
+%
+% GC20 = readtable('trajectory_ana_lab_2_exp_20_transp.csv','PreserveVariableNames',true);
+% [gx20, gy20, gz20, gth20, gt20, gts20] = extractdata(GC20);
+%
+% t20 = linspace(0,min(Gt(end),gt20(end))-1,1e6);
+% ts0 = resample(Gts, t20);
+% ts2 = resample(gts20, t20);
+% ploterrs(ts0, ts2)
+end
+
+[Edata, Gdata] = matchaxes(Gvec{7,1}, Evec{7,1}, 1, 2);
diff --git a/bag/analysys/compare.m b/bag/analysys/compare.m
new file mode 100644
index 0000000..f1a596d
--- /dev/null
+++ b/bag/analysys/compare.m
@@ -0,0 +1,45 @@
+clc; clear; clearvars; close all;
+
+CSVFolder = '../CSV/transp/';
+if ~isfolder(CSVFolder)
+ errorMessage = sprintf('Error: The following folder does not exist:\n%s\nPlease specify a new folder.', myFolder);
+ uiwait(warndlg(errorMessage));
+ myFolder = uigetdir(); % Ask for a new one.
+ if myFolder == 0
+ % User clicked Cancel
+ return;
+ end
+end
+Gvec = [];
+Evec = [];
+myFiles = dir(fullfile(CSVFolder,'*.csv')); %gets all csv files in struct
+for k = 1:length(myFiles)
+ baseFileName = myFiles(k).name;
+ fullFileName = fullfile(CSVFolder, baseFileName);
+ fprintf('Now reading file %s\n', baseFileName);
+ Table = readtable(fullFileName,'PreserveVariableNames',true);
+ if baseFileName(1) == 'G'
+ [Gx, Gy, Gz, Gang, Gt, Gts] = extractGT(Table);
+ Gvec = [Gvec, {baseFileName, Gx, Gy, Gz, Gang, Gt, Gts}'];
+ elseif baseFileName(1) == 'E'
+ [Ex, Ey, Ez, Eang, Et, Ets] = extractdata(Table);
+ Evec = [Evec, {baseFileName, Ex, Ey, Ez, Eang, Et, Ets}'];
+ end
+
+%
+% t10 = linspace(0,min(Gt(end),gt10(end))-1,1e6);
+% ts0 = resample(Gts, t10);
+% ts1 = resample(gts10, t10);
+% ploterrs(ts0, ts1)
+%
+% GC20 = readtable('trajectory_ana_lab_2_exp_20_transp.csv','PreserveVariableNames',true);
+% [gx20, gy20, gz20, gth20, gt20, gts20] = extractdata(GC20);
+%
+% t20 = linspace(0,min(Gt(end),gt20(end))-1,1e6);
+% ts0 = resample(Gts, t20);
+% ts2 = resample(gts20, t20);
+% ploterrs(ts0, ts2)
+end
+
+[Edata, Gdata] = matchaxes(Gvec{7,1}, Evec{7,1}, 2, 3);
+error = vecnorm(Edata(end,:)-Gdata(end,:))
\ No newline at end of file
diff --git a/bag/analysys/dist10.jpg b/bag/analysys/dist10.jpg
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diff --git a/bag/analysys/extractGT.asv b/bag/analysys/extractGT.asv
new file mode 100644
index 0000000..b5467a2
--- /dev/null
+++ b/bag/analysys/extractGT.asv
@@ -0,0 +1,39 @@
+function [Gx, Gy, Gz, Gth, Gt, Gts] = extractGT(GT)
+ t0 = GT(6,2).Var2;
+ GT(1,2).Var2 = (GT(1,2).Var2 - t0)*1e-9;
+ GT(3,2).Var2 = (GT(3,2).Var2 - t0)*1e-9;
+ texpr = 'field.poses\d{1,4}.header.stamp';
+ xexpr = 'field.poses\d{1,4}.pose.position.x';
+ yexpr = 'field.poses\d{1,4}.pose.position.y';
+ zexpr = 'field.poses\d{1,4}.pose.position.z';
+ thexpr = 'field.poses\d{1,4}.pose.orientation.x';
+
+ Gt = [];
+ Gx = [];
+ Gy = [];
+ Gz = [];
+ Gth = [];
+ for i=1:height(GT)
+ if (size(regexp(GT(i,1).Var1{1,1}, texpr)) > 0)
+ GT(i,2).Var2 = (GT(i, 2).Var2 - t0)*1e-9;
+ Gt = [Gt, GT(i,2).Var2];
+ end
+ if (size(regexp(GT(i,1).Var1{1,1}, xexpr)) > 0)
+ Gx = [Gx, GT(i,2).Var2];
+ end
+ if (size(regexp(GT(i,1).Var1{1,1}, yexpr)) > 0)
+ Gy = [Gy, GT(i,2).Var2];
+ end
+ if (size(regexp(GT(i,1).Var1{1,1}, zexpr)) > 0)
+ Gz = [Gz, GT(i,2).Var2];
+ end
+ if (size(regexp(GT(i,1).Var1{1,1}, thexpr)) > 0)
+ [r1 r2 r3] = quat2angle([GT(i+3,2).Var2 GT(i,2).Var2 GT(i+1,2).Var2 GT(i+2,2).Var2]);
+ Gth = [Gth, r1];
+ end
+ end
+
+ Gts = timeseries([Gx' Gy' Gz' Gth'], Gt, 'name', 'groundtruth');
+ Gts.TimeInfo.Units='seconds';
+
+end
\ No newline at end of file
diff --git a/bag/analysys/extractGT.m b/bag/analysys/extractGT.m
new file mode 100644
index 0000000..c410639
--- /dev/null
+++ b/bag/analysys/extractGT.m
@@ -0,0 +1,45 @@
+function [Gx, Gy, Gz, Gang, Gt, Gts] = extractGT(GT)
+ t0 = GT(6,2).Var2;
+ GT(1,2).Var2 = (GT(1,2).Var2 - t0)*1e-9;
+ GT(3,2).Var2 = (GT(3,2).Var2 - t0)*1e-9;
+ texpr = 'field.poses\d{1,4}.header.stamp';
+ xexpr = 'field.poses\d{1,4}.pose.position.x';
+ yexpr = 'field.poses\d{1,4}.pose.position.y';
+ zexpr = 'field.poses\d{1,4}.pose.position.z';
+ thexpr = 'field.poses\d{1,4}.pose.orientation.x';
+
+ Gt = [];
+ Gx = [];
+ Gy = [];
+ Gz = [];
+ Gang = [];
+ for i=1:height(GT)
+ if (size(regexp(GT(i,1).Var1{1,1}, texpr)) > 0)
+ GT(i,2).Var2 = (GT(i, 2).Var2 - t0)*1e-9;
+ Gt = [Gt, GT(i,2).Var2];
+ end
+ if (size(regexp(GT(i,1).Var1{1,1}, xexpr)) > 0)
+ Gx = [Gx, GT(i,2).Var2];
+ end
+ if (size(regexp(GT(i,1).Var1{1,1}, yexpr)) > 0)
+ Gy = [Gy, GT(i,2).Var2];
+ end
+ if (size(regexp(GT(i,1).Var1{1,1}, zexpr)) > 0)
+ Gz = [Gz, GT(i,2).Var2];
+ end
+ if (size(regexp(GT(i,1).Var1{1,1}, thexpr)) > 0)
+ [r1 r2 r3] = quat2angle([GT(i+3,2).Var2 GT(i,2).Var2 GT(i+1,2).Var2 GT(i+2,2).Var2]);
+ Gang = [Gang, [r1 r2 r3]'];
+ end
+ end
+
+ posts = timeseries([Gx' Gy' Gz'], Gt, 'name', 'pos');
+ posts.DataInfo.Units='meters';
+ angts = timeseries(Gang', Gt, 'name', 'ang');
+ angts.DataInfo.Units='radians';
+
+ Gts = tscollection({posts angts}, 'name', 'groundtruth');
+
+ Gts.TimeInfo.Units='seconds';
+ Gts.TimeInfo.Format='SS';
+end
\ No newline at end of file
diff --git a/bag/analysys/extractdata.m b/bag/analysys/extractdata.m
new file mode 100644
index 0000000..082612e
--- /dev/null
+++ b/bag/analysys/extractdata.m
@@ -0,0 +1,32 @@
+function [gx, gy, gz, gang, gt, gts] = extractdata(GC)
+ t0 = GC(2,3).Variables;
+ gx = GC{:,5}';
+ gy = GC{:,6}';
+ gz = GC{:,7}';
+ [R1, R2, R3] = quat2angle([GC{:,11} GC{:,8} GC{:,9} GC{:,10}]);
+ gang = [R1'; R2'; R3'];
+ gt = GC{:,3}';
+ gt = gt-t0;
+ gt = gt*1e-9;
+
+ %remove duplicates
+ [~,~,idx] = unique(gt);
+ gt = accumarray(idx,gt,[],@mean)';
+ gx = accumarray(idx,gx,[],@mean)';
+ gy = accumarray(idx,gy,[],@mean)';
+ gz = accumarray(idx,gz,[],@mean)';
+ gangx = accumarray(idx,gang(1,:),[],@mean);
+ gangy = accumarray(idx,gang(2,:),[],@mean);
+ gangz = accumarray(idx,gang(3,:),[],@mean);
+ gang = [gangx gangy gangz]';
+
+ posts = timeseries([gx' gy' gz'], gt, 'name', 'pos');
+ posts.DataInfo.Units='meters';
+ angts = timeseries(gang', gt, 'name', 'ang');
+ angts.DataInfo.Units='radians';
+
+ gts = tscollection({posts angts}, 'name', 'poses');
+
+ gts.TimeInfo.Units='seconds';
+ gts.TimeInfo.Format='SS';
+end
\ No newline at end of file
diff --git a/bag/analysys/groundtruth_trajectory_lab2.csv b/bag/analysys/groundtruth_trajectory_lab2.csv
new file mode 100644
index 0000000..0ef9d26
--- /dev/null
+++ b/bag/analysys/groundtruth_trajectory_lab2.csv
@@ -0,0 +1,4034 @@
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diff --git a/bag/analysys/interparc.m b/bag/analysys/interparc.m
new file mode 100644
index 0000000..fae3678
--- /dev/null
+++ b/bag/analysys/interparc.m
@@ -0,0 +1,574 @@
+function [pt,dudt,fofthandle] = interparc(t,px,py,varargin)
+% interparc: interpolate points along a curve in 2 or more dimensions
+% usage: pt = interparc(t,px,py) % a 2-d curve
+% usage: pt = interparc(t,px,py,pz) % a 3-d curve
+% usage: pt = interparc(t,px,py,pz,pw,...) % a 4-d or higher dimensional curve
+% usage: pt = interparc(t,px,py,method) % a 2-d curve, method is specified
+% usage: [pt,dudt,fofthandle] = interparc(t,px,py,...) % also returns derivatives, and a function handle
+%
+% Interpolates new points at any fractional point along
+% the curve defined by a list of points in 2 or more
+% dimensions. The curve may be defined by any sequence
+% of non-replicated points.
+%
+% arguments: (input)
+% t - vector of numbers, 0 <= t <= 1, that define
+% the fractional distance along the curve to
+% interpolate the curve at. t = 0 will generate
+% the very first point in the point list, and
+% t = 1 yields the last point in that list.
+% Similarly, t = 0.5 will yield the mid-point
+% on the curve in terms of arc length as the
+% curve is interpolated by a parametric spline.
+%
+% If t is a scalar integer, at least 2, then
+% it specifies the number of equally spaced
+% points in arclength to be generated along
+% the curve.
+%
+% px, py, pz, ... - vectors of length n, defining
+% points along the curve. n must be at least 2.
+% Exact Replicate points should not be present
+% in the curve, although there is no constraint
+% that the curve has replicate independent
+% variables.
+%
+% method - (OPTIONAL) string flag - denotes the method
+% used to compute the points along the curve.
+%
+% method may be any of 'linear', 'spline', or 'pchip',
+% or any simple contraction thereof, such as 'lin',
+% 'sp', or even 'p'.
+%
+% method == 'linear' --> Uses a linear chordal
+% approximation to interpolate the curve.
+% This method is the most efficient.
+%
+% method == 'pchip' --> Uses a parametric pchip
+% approximation for the interpolation
+% in arc length.
+%
+% method == 'spline' --> Uses a parametric spline
+% approximation for the interpolation in
+% arc length. Generally for a smooth curve,
+% this method may be most accurate.
+%
+% method = 'csape' --> if available, this tool will
+% allow a periodic spline fit for closed curves.
+% ONLY use this method if your points should
+% represent a closed curve.
+%
+% If the last point is NOT the same as the
+% first point on the curve, then the curve
+% will be forced to be periodic by this option.
+% That is, the first point will be replicated
+% onto the end.
+%
+% If csape is not present in your matlab release,
+% then an error will result.
+%
+% DEFAULT: 'spline'
+%
+%
+% arguments: (output)
+% pt - Interpolated points at the specified fractional
+% distance (in arc length) along the curve.
+%
+% dudt - when a second return argument is required,
+% interparc will return the parametric derivatives
+% (dx/dt, dy/dt, dz/dt, ...) as an array.
+%
+% fofthandle - a function handle, taking numbers in the interval [0,1]
+% and evaluating the function at those points.
+%
+% Extrapolation will not be permitted by this call.
+% Any values of t that lie outside of the interval [0,1]
+% will be clipped to the endpoints of the curve.
+%
+% Example:
+% % Interpolate a set of unequally spaced points around
+% % the perimeter of a unit circle, generating equally
+% % spaced points around the perimeter.
+% theta = sort(rand(15,1))*2*pi;
+% theta(end+1) = theta(1);
+% px = cos(theta);
+% py = sin(theta);
+%
+% % interpolate using parametric splines
+% pt = interparc(100,px,py,'spline');
+%
+% % Plot the result
+% plot(px,py,'r*',pt(:,1),pt(:,2),'b-o')
+% axis([-1.1 1.1 -1.1 1.1])
+% axis equal
+% grid on
+% xlabel X
+% ylabel Y
+% title 'Points in blue are uniform in arclength around the circle'
+%
+%
+% Example:
+% % For the previous set of points, generate exactly 6
+% % points around the parametric splines, verifying
+% % the uniformity of the arc length interpolant.
+% pt = interparc(6,px,py,'spline');
+%
+% % Convert back to polar form. See that the radius
+% % is indeed 1, quite accurately.
+% [TH,R] = cart2pol(pt(:,1),pt(:,2))
+% % TH =
+% % 0.86005
+% % 2.1141
+% % -2.9117
+% % -1.654
+% % -0.39649
+% % 0.86005
+% % R =
+% % 1
+% % 0.9997
+% % 0.9998
+% % 0.99999
+% % 1.0001
+% % 1
+%
+% % Unwrap the polar angles, and difference them.
+% diff(unwrap(TH))
+% % ans =
+% % 1.2541
+% % 1.2573
+% % 1.2577
+% % 1.2575
+% % 1.2565
+%
+% % Six points around the circle should be separated by
+% % 2*pi/5 radians, if they were perfectly uniform. The
+% % slight differences are due to the imperfect accuracy
+% % of the parametric splines.
+% 2*pi/5
+% % ans =
+% % 1.2566
+%
+%
+% See also: arclength, spline, pchip, interp1
+%
+% Author: John D'Errico
+% e-mail: woodchips@rochester.rr.com
+% Release: 1.0
+% Release date: 3/15/2010
+
+% unpack the arguments and check for errors
+if nargin < 3
+ error('ARCLENGTH:insufficientarguments', ...
+ 'at least t, px, and py must be supplied')
+end
+
+t = t(:);
+if (numel(t) == 1) && (t > 1) && (rem(t,1) == 0)
+ % t specifies the number of points to be generated
+ % equally spaced in arclength
+ t = linspace(0,1,t)';
+elseif any(t < 0) || any(t > 1)
+ error('ARCLENGTH:impropert', ...
+ 'All elements of t must be 0 <= t <= 1')
+end
+
+% how many points will be interpolated?
+nt = numel(t);
+
+% the number of points on the curve itself
+px = px(:);
+py = py(:);
+n = numel(px);
+
+% are px and py both vectors of the same length?
+if ~isvector(px) || ~isvector(py) || (length(py) ~= n)
+ error('ARCLENGTH:improperpxorpy', ...
+ 'px and py must be vectors of the same length')
+elseif n < 2
+ error('ARCLENGTH:improperpxorpy', ...
+ 'px and py must be vectors of length at least 2')
+end
+
+% compose px and py into a single array. this way,
+% if more dimensions are provided, the extension
+% is trivial.
+pxy = [px,py];
+ndim = 2;
+
+% the default method is 'linear'
+method = 'spline';
+
+% are there any other arguments?
+if nargin > 3
+ % there are. check the last argument. Is it a string?
+ if ischar(varargin{end})
+ method = varargin{end};
+ varargin(end) = [];
+
+ % method may be any of {'linear', 'pchip', 'spline', 'csape'.}
+ % any any simple contraction thereof.
+ valid = {'linear', 'pchip', 'spline', 'csape'};
+ [method,errstr] = validstring(method,valid);
+ if ~isempty(errstr)
+ error('INTERPARC:incorrectmethod',errstr)
+ end
+ end
+
+ % anything that remains in varargin must add
+ % an additional dimension on the curve/polygon
+ for i = 1:numel(varargin)
+ pz = varargin{i};
+ pz = pz(:);
+ if numel(pz) ~= n
+ error('ARCLENGTH:improperpxorpy', ...
+ 'pz must be of the same size as px and py')
+ end
+ pxy = [pxy,pz]; %#ok
+ end
+
+ % the final number of dimensions provided
+ ndim = size(pxy,2);
+end
+
+% if csape, then make sure the first point is replicated at the end.
+% also test to see if csape is available
+if method(1) == 'c'
+ if exist('csape','file') == 0
+ error('CSAPE was requested, but you lack the necessary toolbox.')
+ end
+
+ p1 = pxy(1,:);
+ pend = pxy(end,:);
+
+ % get a tolerance on whether the first point is replicated.
+ if norm(p1 - pend) > 10*eps(norm(max(abs(pxy),[],1)))
+ % the two end points were not identical, so wrap the curve
+ pxy(end+1,:) = p1;
+ nt = nt + 1;
+ end
+end
+
+% preallocate the result, pt
+pt = NaN(nt,ndim);
+
+% Compute the chordal (linear) arclength
+% of each segment. This will be needed for
+% any of the methods.
+chordlen = sqrt(sum(diff(pxy,[],1).^2,2));
+
+% Normalize the arclengths to a unit total
+chordlen = chordlen/sum(chordlen);
+
+% cumulative arclength
+cumarc = [0;cumsum(chordlen)];
+
+% The linear interpolant is trivial. do it as a special case
+if method(1) == 'l'
+ % The linear method.
+
+ % which interval did each point fall in, in
+ % terms of t?
+ [junk,tbins] = histc(t,cumarc); %#ok
+
+ % catch any problems at the ends
+ tbins((tbins <= 0) | (t <= 0)) = 1;
+ tbins((tbins >= n) | (t >= 1)) = n - 1;
+
+ % interpolate
+ s = (t - cumarc(tbins))./chordlen(tbins);
+ % be nice, and allow the code to work on older releases
+ % that don't have bsxfun
+ pt = pxy(tbins,:) + (pxy(tbins+1,:) - pxy(tbins,:)).*repmat(s,1,ndim);
+
+ % do we need to compute derivatives here?
+ if nargout > 1
+ dudt = (pxy(tbins+1,:) - pxy(tbins,:))./repmat(chordlen(tbins),1,ndim);
+ end
+
+ % do we need to create the spline as a piecewise linear function?
+ if nargout > 2
+ spl = cell(1,ndim);
+ for i = 1:ndim
+ coefs = [diff(pxy(:,i))./diff(cumarc),pxy(1:(end-1),i)];
+ spl{i} = mkpp(cumarc.',coefs);
+ end
+
+ %create a function handle for evaluation, passing in the splines
+ fofthandle = @(t) foft(t,spl);
+ end
+
+ % we are done at this point
+ return
+end
+
+% If we drop down to here, we have either a spline
+% or csape or pchip interpolant to work with.
+
+% compute parametric splines
+spl = cell(1,ndim);
+spld = spl;
+diffarray = [3 0 0;0 2 0;0 0 1;0 0 0];
+for i = 1:ndim
+ switch method
+ case 'pchip'
+ spl{i} = pchip(cumarc,pxy(:,i));
+ case 'spline'
+ spl{i} = spline(cumarc,pxy(:,i));
+ nc = numel(spl{i}.coefs);
+ if nc < 4
+ % just pretend it has cubic segments
+ spl{i}.coefs = [zeros(1,4-nc),spl{i}.coefs];
+ spl{i}.order = 4;
+ end
+ case 'csape'
+ % csape was specified, so the curve is presumed closed,
+ % therefore periodic
+ spl{i} = csape(cumarc,pxy(:,i),'periodic');
+ nc = numel(spl{i}.coefs);
+ if nc < 4
+ % just pretend it has cubic segments
+ spl{i}.coefs = [zeros(1,4-nc),spl{i}.coefs];
+ spl{i}.order = 4;
+ end
+ end
+
+ % and now differentiate them
+ xp = spl{i};
+ xp.coefs = xp.coefs*diffarray;
+ xp.order = 3;
+ spld{i} = xp;
+end
+
+% catch the case where there were exactly three points
+% in the curve, and spline was used to generate the
+% interpolant. In this case, spline creates a curve with
+% only one piece, not two.
+if (numel(cumarc) == 3) && (method(1) == 's')
+ cumarc = spl{1}.breaks;
+ n = numel(cumarc);
+ chordlen = sum(chordlen);
+end
+
+% Generate the total arclength along the curve
+% by integrating each segment and summing the
+% results. The integration scheme does its job
+% using an ode solver.
+
+% polyarray here contains the derivative polynomials
+% for each spline in a given segment
+polyarray = zeros(ndim,3);
+seglen = zeros(n-1,1);
+
+% options for ode45
+opts = odeset('reltol',1.e-9);
+for i = 1:spl{1}.pieces
+ % extract polynomials for the derivatives
+ for j = 1:ndim
+ polyarray(j,:) = spld{j}.coefs(i,:);
+ end
+
+ % integrate the arclength for the i'th segment
+ % using ode45 for the integral. I could have
+ % done this part with quad too, but then it
+ % would not have been perfectly (numerically)
+ % consistent with the next operation in this tool.
+ [tout,yout] = ode45(@(t,y) segkernel(t,y),[0,chordlen(i)],0,opts); %#ok
+ seglen(i) = yout(end);
+end
+
+% and normalize the segments to have unit total length
+totalsplinelength = sum(seglen);
+cumseglen = [0;cumsum(seglen)];
+
+% which interval did each point fall into, in
+% terms of t, but relative to the cumulative
+% arc lengths along the parametric spline?
+[junk,tbins] = histc(t*totalsplinelength,cumseglen); %#ok
+
+% catch any problems at the ends
+tbins((tbins <= 0) | (t <= 0)) = 1;
+tbins((tbins >= n) | (t >= 1)) = n - 1;
+
+% Do the fractional integration within each segment
+% for the interpolated points. t is the parameter
+% used to define the splines. It is defined in terms
+% of a linear chordal arclength. This works nicely when
+% a linear piecewise interpolant was used. However,
+% what is asked for is an arclength interpolation
+% in terms of arclength of the spline itself. Call s
+% the arclength traveled along the spline.
+s = totalsplinelength*t;
+
+% the ode45 options will now include an events property
+% so we can catch zero crossings.
+opts = odeset('reltol',1.e-9,'events',@ode_events);
+
+ti = t;
+for i = 1:nt
+ % si is the piece of arc length that we will look
+ % for in this spline segment.
+ si = s(i) - cumseglen(tbins(i));
+
+ % extract polynomials for the derivatives
+ % in the interval the point lies in
+ for j = 1:ndim
+ polyarray(j,:) = spld{j}.coefs(tbins(i),:);
+ end
+
+ % we need to integrate in t, until the integral
+ % crosses the specified value of si. Because we
+ % have defined totalsplinelength, the lengths will
+ % be normalized at this point to a unit length.
+ %
+ % Start the ode solver at -si, so we will just
+ % look for an event where y crosses zero.
+ [tout,yout,te,ye] = ode45(@(t,y) segkernel(t,y),[0,chordlen(tbins(i))],-si,opts); %#ok
+
+ % we only need that point where a zero crossing occurred
+ % if no crossing was found, then we can look at each end.
+ if ~isempty(te)
+ ti(i) = te(1) + cumarc(tbins(i));
+ else
+ % a crossing must have happened at the very
+ % beginning or the end, and the ode solver
+ % missed it, not trapping that event.
+ if abs(yout(1)) < abs(yout(end))
+ % the event must have been at the start.
+ ti(i) = tout(1) + cumarc(tbins(i));
+ else
+ % the event must have been at the end.
+ ti(i) = tout(end) + cumarc(tbins(i));
+ end
+ end
+end
+
+% Interpolate the parametric splines at ti to get
+% our interpolated value.
+for L = 1:ndim
+ pt(:,L) = ppval(spl{L},ti);
+end
+
+% do we need to compute first derivatives here at each point?
+if nargout > 1
+ dudt = zeros(nt,ndim);
+ for L = 1:ndim
+ dudt(:,L) = ppval(spld{L},ti);
+ end
+end
+
+% create a function handle for evaluation, passing in the splines
+if nargout > 2
+ fofthandle = @(t) foft(t,spl);
+end
+
+% ===============================================
+% nested function for the integration kernel
+% ===============================================
+ function val = segkernel(t,y) %#ok
+ % sqrt((dx/dt)^2 + (dy/dt)^2 + ...)
+ val = zeros(size(t));
+ for k = 1:ndim
+ val = val + polyval(polyarray(k,:),t).^2;
+ end
+ val = sqrt(val);
+
+ end % function segkernel
+
+% ===============================================
+% nested function for ode45 integration events
+% ===============================================
+ function [value,isterminal,direction] = ode_events(t,y) %#ok
+ % ode event trap, looking for zero crossings of y.
+ value = y;
+ isterminal = ones(size(y));
+ direction = ones(size(y));
+ end % function ode_events
+
+end % mainline - interparc
+
+
+% ===============================================
+% end mainline - interparc
+% ===============================================
+% begin subfunctions
+% ===============================================
+
+% ===============================================
+% subfunction for evaluation at any point externally
+% ===============================================
+function f_t = foft(t,spl)
+% tool allowing the user to evaluate the interpolant at any given point for any values t in [0,1]
+pdim = numel(spl);
+f_t = zeros(numel(t),pdim);
+
+% convert t to a column vector, clipping it to [0,1] as we do.
+t = max(0,min(1,t(:)));
+
+% just loop over the splines in the cell array of splines
+for i = 1:pdim
+ f_t(:,i) = ppval(spl{i},t);
+end
+end % function foft
+
+
+function [str,errorclass] = validstring(arg,valid)
+% validstring: compares a string against a set of valid options
+% usage: [str,errorclass] = validstring(arg,valid)
+%
+% If a direct hit, or any unambiguous shortening is found, that
+% string is returned. Capitalization is ignored.
+%
+% arguments: (input)
+% arg - character string, to be tested against a list
+% of valid choices. Capitalization is ignored.
+%
+% valid - cellstring array of alternative choices
+%
+% Arguments: (output)
+% str - string - resulting choice resolved from the
+% list of valid arguments. If no unambiguous
+% choice can be resolved, then str will be empty.
+%
+% errorclass - string - A string argument that explains
+% the error. It will be one of the following
+% possibilities:
+%
+% '' --> No error. An unambiguous match for arg
+% was found among the choices.
+%
+% 'No match found' --> No match was found among
+% the choices provided in valid.
+%
+% 'Ambiguous argument' --> At least two ambiguous
+% matches were found among those provided
+% in valid.
+%
+%
+% Example:
+% valid = {'off' 'on' 'The sky is falling'}
+%
+%
+% See also: parse_pv_pairs, strmatch, strcmpi
+%
+% Author: John D'Errico
+% e-mail: woodchips@rochester.rr.com
+% Release: 1.0
+% Release date: 3/25/2010
+
+ind = find(strncmpi(lower(arg),valid,numel(arg)));
+if isempty(ind)
+ % No hit found
+ errorclass = 'No match found';
+ str = '';
+elseif (length(ind) > 1)
+ % Ambiguous arg, hitting more than one of the valid options
+ errorclass = 'Ambiguous argument';
+ str = '';
+ return
+else
+ errorclass = '';
+ str = valid{ind};
+end
+
+end % function validstring
+
diff --git a/bag/analysys/matchaxes.asv b/bag/analysys/matchaxes.asv
new file mode 100644
index 0000000..96b92d3
--- /dev/null
+++ b/bag/analysys/matchaxes.asv
@@ -0,0 +1,24 @@
+function matchaxes(GT, TS, t0, t1)
+ [GTpos TSpos] = synchronize(GT.pos, TS.pos, 'Intersection');
+ [GTang TSang] = synchronize(GT.ang, TS.ang, 'Union');
+ GT = tscollection({GTpos GTang});
+ TS = tscollection({TSpos TSang});
+ Gpos = getsampleusingtime(GT, GT.Time(t0), GT.Time(t1)).pos.Data;
+ Tpos = getsampleusingtime(TS, GT.Time(t0), GT.Time(t1)).pos.Data;
+ Tt = getsampleusingtime(TS, GT.Time(t0), GT.Time(t1)).Time;
+ Gt = getsampleusingtime(GT, GT.Time(t0), GT.Time(t1)).Time;
+ Grot = getsampleusingtime(GT, GT.Time(t0), GT.Time(t1)).ang.Data;
+ Trot = getsampleusingtime(TS, GT.Time(t0), GT.Time(t1)).ang.Data;
+
+ rotangles = Grot(1,:)-Trot(1,:)
+ rotmatrix = eul2rotm(rotangles)
+ Tpos_at_origin = (Tpos - Tpos(1,:));
+ Tpos_rotated_at_origin = Tpos_at_origin*rotmatrix;
+ Tpos_at_Gpos_origin = Tpos_rotated_at_origin + Gpos(1,:);
+
+ figure
+ plot(Gt, Gpos)
+ hold on
+ plot(Tt, Tpos_at_Gpos_origin)
+
+end
\ No newline at end of file
diff --git a/bag/analysys/matchaxes.m b/bag/analysys/matchaxes.m
new file mode 100644
index 0000000..98fccce
--- /dev/null
+++ b/bag/analysys/matchaxes.m
@@ -0,0 +1,22 @@
+function [Tpos_at_Gpos_origin, Gdata] = matchaxes(GT, TS, t0, t1)
+ Gpos = getsampleusingtime(GT, GT.Time(t0), GT.Time(t1)).pos;
+ Tpos = getsampleusingtime(TS, GT.Time(t0), GT.Time(t1)).pos;
+ [Gpos, Tpos] = synchronize(Gpos, Tpos, 'Union', 'KeepOriginalTimes',true);
+
+ Grot = getsampleusingtime(GT, GT.Time(t0), GT.Time(t1)).ang;
+ Trot = getsampleusingtime(TS, GT.Time(t0), GT.Time(t1)).ang;
+ [Grot, Trot] = synchronize(Grot, Trot, 'Union', 'KeepOriginalTimes',true');
+
+ Tt = Tpos.Time;
+ Gt = Gpos.Time;
+
+
+ rotangles = Grot.Data(1,:)-Trot.Data(1,:);
+ rotmatrix = eul2rotm(rotangles);
+ Tpos_at_origin = (Tpos.Data - Tpos.Data(1,:));
+ Tpos_rotated_at_origin = Tpos_at_origin*rotmatrix;
+
+ Tpos_at_Gpos_origin = Tpos_rotated_at_origin + Gpos.Data(1,:);
+ Gdata = Gpos.Data;
+
+end
\ No newline at end of file
diff --git a/bag/analysys/ploterrs.m b/bag/analysys/ploterrs.m
new file mode 100644
index 0000000..ae6d994
--- /dev/null
+++ b/bag/analysys/ploterrs.m
@@ -0,0 +1,26 @@
+function ploterrs(ts0, ts)
+ edist = ts.pos - ts0.pos;
+ eang = ts.ang - ts0.ang;
+ edist.name='Distance error';
+ eang.name='Angular error';
+ edist.DataInfo.Units='meters';
+ eang.DataInfo.Units='radians';
+ edist.TimeInfo.Units='seconds';
+ edist.TimeInfo.Format='SS';
+ eang.TimeInfo.Units='seconds';
+ eang.TimeInfo.Format='SS';
+
+ %Plot norm of position
+ figure
+ plot(edist.Time, vecnorm([edist.Data(:,1)'; edist.Data(:,2)'; edist.Data(:,3)']))
+ title(edist.name)
+ xlabel(edist.TimeInfo.Units)
+ ylabel(edist.DataInfo.Units)
+
+ %Plot error of angle
+ figure
+ plot(eang.Time, abs(eang.Data))
+ title(eang.name)
+ xlabel(eang.TimeInfo.Units)
+ ylabel(eang.DataInfo.Units)
+end
\ No newline at end of file
diff --git a/bag/generate_trajectory_csv.bash b/bag/generate_trajectory_csv.bash
index b1b55b3..1657228 100644
--- a/bag/generate_trajectory_csv.bash
+++ b/bag/generate_trajectory_csv.bash
@@ -13,8 +13,8 @@ fi
# Starting with E ==> experiment, we extract the poses
for yamlfile in $(find ../yaml/trajectory_analysys -maxdepth 1 -type f -printf "%f\n")
do
- rm recordings/trajectory_recording$yamlname.bag
yamlname=${yamlfile%.*}
+ rm recordings/trajectory_recording$yamlname.bag
roslaunch wolf_demo_imu2d imu2d_analysys.launch bag:=$BAG\_filtered_notf test:=$yamlfile speed:=1 suffix:=$yamlname rviz:=false
if [[ ${yamlname:0:1} == 'G' ]]
then
@@ -25,12 +25,15 @@ do
rm CSV/$yamlname.csv
rostopic echo -b recordings/trajectory_recording$yamlname\_tmp.bag /wolf_ros_node/trajectory -p > CSV/$yamlname.csv
rm recordings/trajectory_recording$yamlname\_tmp.bag
+
+ rm CSV/transp/$yamlname\_transp.csv
+ python3 transpose_csv.py CSV/$yamlname.csv CSV/transp/$yamlname\_transp.csv
+
elif [[ ${yamlname:0:1} == 'E' ]]
then
rm CSV/$yamlname.csv
rostopic echo -b recordings/trajectory_recording$yamlname.bag /wolf_ros_node/pose_pose_with_cov -p > CSV/$yamlname.csv
+ cp CSV/$yamlname.csv CSV/transp/$yamlname\_transp.csv
fi
- rm CSV/transp/$yamlname\_transp.csv
- python3 transpose_csv.py CSV/$yamlname.csv CSV/transp/$yamlname\_transp.csv
done
diff --git a/bag/transpose_csv.py b/bag/transpose_csv.py
index 75296bd..f897827 100644
--- a/bag/transpose_csv.py
+++ b/bag/transpose_csv.py
@@ -1,7 +1,7 @@
import pandas as pd
import sys
def transpose(in_bag, out_bag):
- pd.read_csv(in_bag, header=None).T.to_csv(out_bag, header=False, index=False)
+ pd.read_csv(in_bag, header=None, dtype='unicode').T.to_csv(out_bag, header=False, index=False)
if __name__ == '__main__':
in_bag = sys.argv[1]
diff --git a/yaml/trajectory_analysys/E-1_0.yaml b/yaml/trajectory_analysys/E-1_0.yaml
index 09e4919..2dd84db 100644
--- a/yaml/trajectory_analysys/E-1_0.yaml
+++ b/yaml/trajectory_analysys/E-1_0.yaml
@@ -1,7 +1,7 @@
config:
debug:
profiling: true
- profiling_file: "~/wolf_demo_profiling_imu2d_test5.txt"
+ profiling_file: "~/profiling/wolf_demo_profiling_E-1_0.txt"
print_problem: false
print_period: 2
print_depth: 4
@@ -137,7 +137,7 @@ config:
type: "PublisherPose"
topic: "pose"
extrinsics: false
- period: 0.005
+ period: 0.01
frame_id: "map"
-
package: "wolf_ros_laser"
diff --git a/yaml/trajectory_analysys/G-1_0.yaml b/yaml/trajectory_analysys/G-1_0.yaml
index 7c0cf8e..ffc545a 100644
--- a/yaml/trajectory_analysys/G-1_0.yaml
+++ b/yaml/trajectory_analysys/G-1_0.yaml
@@ -1,7 +1,7 @@
config:
debug:
profiling: true
- profiling_file: "~/wolf_demo_profiling_imu2d_test0.txt"
+ profiling_file: "~/profiling/wolf_demo_profiling_G-1_0.txt"
print_problem: false
print_period: 2
print_depth: 4
diff --git a/yaml/trajectory_analysys/hold/E-0_1.yaml b/yaml/trajectory_analysys/hold/E-0_1.yaml
new file mode 100644
index 0000000..fb7d5a1
--- /dev/null
+++ b/yaml/trajectory_analysys/hold/E-0_1.yaml
@@ -0,0 +1,157 @@
+config:
+ debug:
+ profiling: true
+ profiling_file: "~/profiling/wolf_demo_profiling_E-0_1.txt"
+ print_problem: false
+ print_period: 2
+ print_depth: 4
+ print_constr_by: false
+ print_metric: true
+ print_state_blocks: true
+ problem:
+ tree_manager:
+ type: "none"
+ frame_structure: "POV"
+ dimension: 2
+ prior:
+ mode: "fix"
+ $state:
+ P: [0,0]
+ O: [0]
+ V: [0,0]
+ time_tolerance: 0.1
+ node_rate: 100
+ map:
+ type: "MapBase"
+ plugin: "core"
+
+ solver:
+ follow: "parameters/solver.yaml"
+
+
+ sensors:
+ -
+ type: "SensorLaser2d"
+ name: "scanner_front_left"
+ plugin: "laser"
+ follow: "parameters/test_laser_params.yaml"
+ -
+ type: "SensorImu2d"
+ name: "bno"
+ plugin: "imu"
+ follow: "parameters/test_imu_params_bno.yaml"
+ -
+ type: "SensorImu2d"
+ name: "microstrain"
+ plugin: "imu"
+ follow: "parameters/test_imu_params_microstrain.yaml"
+
+ processors:
+ -
+ type: "ProcessorOdomIcp"
+ name: "processorodomicp"
+ sensor_name: "scanner_front_left"
+ plugin: "laser"
+ keyframe_vote:
+ voting_active: true
+ min_features_for_keyframe: 10
+ min_dist: 999
+ min_angle: 999
+ min_time: 0.1
+ min_error: 999
+ max_points: 0
+ follow: "parameters/test_laser_processor.yaml"
+ #-
+ # type: "ProcessorLoopClosureIcp"
+ # name: "processorloopclosureicp"
+ # sensor_name: "scanner_front_left"
+ # plugin: "laser"
+ # time_tolerance: 0.1
+ # apply_loss_function: true
+ # keyframe_vote:
+ # voting_active: false
+ # recent_frames_ignored: 10
+ # frames_ignored_after_loop: 0
+ # max_error_threshold: 0.02
+ # min_points_percent: 40
+ # max_loops: 1
+ # max_candidates: 5
+ # max_attempts: 5
+ # candidate_generation: "random" # 'random' or 'tree'
+ # icp:
+ # follow: "parameters/csm.yaml"
+ -
+ type: "ProcessorImu2d"
+ name: "processorimu2dbno"
+ sensor_name: "bno"
+ plugin: "imu"
+ follow: "parameters/test_imu_processor_bno.yaml"
+ -
+ type: "ProcessorImu2d"
+ name: "processorimu2dmicro"
+ sensor_name: "microstrain"
+ plugin: "imu"
+ follow: "parameters/test_imu_processor_microstrain.yaml"
+
+ ROS subscriber:
+ -
+ package: "wolf_ros_laser"
+ type: "SubscriberLaser2d"
+ topic: "/ana/sensors/scan"
+ sensor_name: "scanner_front_left"
+ load_params_from_msg: true
+ #-
+ # package: "wolf_ros_imu"
+ # type: "SubscriberImuEnableable"
+ # topic: "/ana/sensors/bno055_imu/imumal"
+ # sensor_name: "bno"
+ # follow: "parameters/test_imu_subscriber_bno.yaml"
+ -
+ package: "wolf_ros_imu"
+ type: "SubscriberImuEnableable"
+ topic: "/ana/imu/data"
+ sensor_name: "microstrain"
+ follow: "parameters/test_imu_subscriber_microstrain.yaml"
+
+ ROS publisher:
+ -
+ package: "wolf_ros_node"
+ type: "PublisherTf"
+ topic: " "
+ period: 0.1
+ follow: "parameters/test_publisher_ros_node.yaml"
+ -
+ package: "wolf_ros_node"
+ type: "PublisherGraph"
+ topic: "graph"
+ period: 1
+ viz_overlapped_factors: true
+ -
+ package: "wolf_ros_node"
+ type: "PublisherTrajectory"
+ topic: "trajectory"
+ period: 1
+ frame_id: "map"
+ -
+ package: "wolf_ros_node"
+ type: "PublisherPose"
+ topic: "pose"
+ extrinsics: false
+ period: 0.005
+ frame_id: "map"
+ -
+ package: "wolf_ros_laser"
+ type: "PublisherLaserMap"
+ topic: "map"
+ period: 1
+ map_frame_id: "map"
+ update_dist_th: 0.05
+ update_angle_th: 0.05
+ max_n_cells: 1000000
+ grid_size: 0.1
+ p_free: 0.3
+ p_obst: 0.8
+ p_free_th: 0.2
+ p_obst_th: 0.9
+ discard_max_range: true
+
diff --git a/yaml/trajectory_analysys/hold/G-0_1.yaml b/yaml/trajectory_analysys/hold/G-0_1.yaml
new file mode 100644
index 0000000..0d39fd8
--- /dev/null
+++ b/yaml/trajectory_analysys/hold/G-0_1.yaml
@@ -0,0 +1,115 @@
+config:
+ debug:
+ profiling: true
+ profiling_file: "~/profiling/wolf_demo_profiling_G-0_1.txt"
+ print_problem: false
+ print_period: 2
+ print_depth: 4
+ print_constr_by: false
+ print_metric: true
+ print_state_blocks: true
+ problem:
+ tree_manager:
+ type: "none"
+ frame_structure: "POV"
+ dimension: 2
+ prior:
+ mode: "fix"
+ $state:
+ P: [0,0]
+ O: [0]
+ V: [0,0]
+ time_tolerance: 0.1
+ node_rate: 100
+ map:
+ type: "MapBase"
+ plugin: "core"
+
+ solver:
+ follow: "parameters/solver.yaml"
+
+ sensors:
+ -
+ type: "SensorLaser2d"
+ name: "scanner_front_left"
+ plugin: "laser"
+ follow: "parameters/test_laser_params.yaml"
+
+ processors:
+ -
+ type: "ProcessorOdomIcp"
+ name: "processorodomicp"
+ sensor_name: "scanner_front_left"
+ plugin: "laser"
+ keyframe_vote:
+ voting_active: true
+ min_features_for_keyframe: 10
+ min_dist: 999
+ min_angle: 999
+ min_time: 0.1
+ min_error: 999
+ max_points: 0
+ follow: "parameters/test_laser_processor.yaml"
+ #-
+ # type: "ProcessorLoopClosureIcp"
+ # name: "processorloopclosureicp"
+ # sensor_name: "scanner_front_left"
+ # plugin: "laser"
+ # time_tolerance: 0.1
+ # apply_loss_function: true
+ # keyframe_vote:
+ # voting_active: false
+ # recent_frames_ignored: 3
+ # frames_ignored_after_loop: 0
+ # max_error_threshold: 0.02
+ # min_points_percent: 40
+ # max_loops: 3
+ # max_candidates: 5
+ # max_attempts: 15
+ # candidate_generation: "random" # 'random' or 'tree'
+ # icp:
+ # follow: "parameters/csm.yaml"
+
+
+ ROS subscriber:
+ -
+ package: "wolf_ros_laser"
+ type: "SubscriberLaser2d"
+ topic: "/ana/sensors/scan"
+ sensor_name: "scanner_front_left"
+ load_params_from_msg: true
+
+ ROS publisher:
+ -
+ package: "wolf_ros_node"
+ type: "PublisherTf"
+ topic: " "
+ period: 0.1
+ follow: "parameters/test_publisher_ros_node.yaml"
+ -
+ package: "wolf_ros_node"
+ type: "PublisherGraph"
+ topic: "graph"
+ period: 1
+ viz_overlapped_factors: true
+ -
+ package: "wolf_ros_node"
+ type: "PublisherTrajectory"
+ topic: "trajectory"
+ period: 1
+ frame_id: "map"
+ -
+ package: "wolf_ros_laser"
+ type: "PublisherLaserMap"
+ topic: "map"
+ period: 1
+ map_frame_id: "map"
+ update_dist_th: 0.05
+ update_angle_th: 0.05
+ max_n_cells: 1000000
+ grid_size: 0.1
+ p_free: 0.3
+ p_obst: 0.8
+ p_free_th: 0.2
+ p_obst_th: 0.9
+ discard_max_range: true
--
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