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Merged duplicate Pose2SLAMExample_graph.m examples in different directories

release/4.3a0
Richard Roberts 2012-07-30 18:34:50 +00:00
parent a13ef97987
commit da1a732eff
2 changed files with 4 additions and 48 deletions
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47
examples/Pose2SLAMExample_graph.m
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@ -1,47 +0,0 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% GTSAM Copyright 2010, Georgia Tech Research Corporation,
% Atlanta, Georgia 30332-0415
% All Rights Reserved
% Authors: Frank Dellaert, et al. (see THANKS for the full author list)
%
% See LICENSE for the license information
%
% @brief Read graph from file and perform GraphSLAM
% @author Frank Dellaert
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Initialize graph, initial estimate, and odometry noise
import gtsam.*
model = noiseModel.Diagonal.Sigmas([0.05; 0.05; 5*pi/180]);
maxID = 0;
addNoise = false;
smart = true;
[graph,initial]=load2D('Data/w100-odom.graph',model,maxID,addNoise,smart);
initial.print(sprintf('Initial estimate:\n'));
%% Add a Gaussian prior on pose x_1
import gtsam.*
priorMean = Pose2(0.0, 0.0, 0.0); % prior mean is at origin
priorNoise = noiseModel.Diagonal.Sigmas([0.01; 0.01; 0.01]);
graph.addPosePrior(0, priorMean, priorNoise); % add directly to graph
%% Plot Initial Estimate
figure(1);clf
P=initial.poses;
plot(P(:,1),P(:,2),'g-*'); axis equal
%% Optimize using Levenberg-Marquardt optimization with an ordering from colamd
result = graph.optimize(initial,1);
P=result.poses;
hold on; plot(P(:,1),P(:,2),'b-*')
result.print(sprintf('\nFinal result:\n'));
%% Plot Covariance Ellipses
marginals = graph.marginals(result);
P={};
for i=1:result.size()-1
pose_i = result.pose(i);
P{i}=marginals.marginalCovariance(i);
plotPose2(pose_i,'b',P{i})
end
fprintf(1,'%.5f %.5f %.5f\n',P{99})

5
matlab/gtsam_examples/Pose2SLAMExample_graph.m
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@ -16,7 +16,10 @@ datafile = gtsam_utils.findExampleDataFile('w100-odom.graph');
%% Initialize graph, initial estimate, and odometry noise %% Initialize graph, initial estimate, and odometry noise
import gtsam.* import gtsam.*
model = noiseModel.Diagonal.Sigmas([0.05; 0.05; 5*pi/180]); model = noiseModel.Diagonal.Sigmas([0.05; 0.05; 5*pi/180]);
[graph,initial] = gtsam_utils.load2D(datafile, model); maxID = 0;
addNoise = false;
smart = true;
[graph,initial] = gtsam.load2D(datafile, model, maxID, addNoise, smart);
initial.print(sprintf('Initial estimate:\n')); initial.print(sprintf('Initial estimate:\n'));
%% Add a Gaussian prior on pose x_1 %% Add a Gaussian prior on pose x_1