%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % 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 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% import gtsam.* %% Create a hexagon of poses hexagon = circlePose2(6,1.0); p0 = hexagon.at(0); p1 = hexagon.at(1); %% create a Pose graph with one equality constraint and one measurement fg = NonlinearFactorGraph; fg.add(NonlinearEqualityPose2(0, p0)); delta = p0.between(p1); covariance = noiseModel.Diagonal.Sigmas([0.05; 0.05; 5*pi/180]); fg.add(BetweenFactorPose2(0,1, delta, covariance)); fg.add(BetweenFactorPose2(1,2, delta, covariance)); fg.add(BetweenFactorPose2(2,3, delta, covariance)); fg.add(BetweenFactorPose2(3,4, delta, covariance)); fg.add(BetweenFactorPose2(4,5, delta, covariance)); fg.add(BetweenFactorPose2(5,0, delta, covariance)); %% Create initial config initial = Values; initial.insert(0, p0); initial.insert(1, hexagon.at(1).retract([-0.1, 0.1,-0.1]')); initial.insert(2, hexagon.at(2).retract([ 0.1,-0.1, 0.1]')); initial.insert(3, hexagon.at(3).retract([-0.1, 0.1,-0.1]')); initial.insert(4, hexagon.at(4).retract([ 0.1,-0.1, 0.1]')); initial.insert(5, hexagon.at(5).retract([-0.1, 0.1,-0.1]')); %% Plot Initial Estimate cla plot2DTrajectory(initial, 'g*-'); axis equal %% optimize optimizer = DoglegOptimizer(fg, initial); result = optimizer.optimizeSafely; %% Show Result hold on; plot2DTrajectory(result, 'b*-'); view(2); axis([-1.5 1.5 -1.5 1.5]); result.print(sprintf('\nFinal result:\n'));