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										 |  |  | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | 
					
						
							|  |  |  | % 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 | 
					
						
							|  |  |  | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% | 
					
						
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										 |  |  | import gtsam.* | 
					
						
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							|  |  |  | %% Create a hexagon of poses | 
					
						
							|  |  |  | hexagon = circlePose2(6,1.0); | 
					
						
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										 |  |  | p0 = hexagon.atPose2(0); | 
					
						
							|  |  |  | p1 = hexagon.atPose2(1); | 
					
						
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							|  |  |  | %% create a Pose graph with one equality constraint and one measurement | 
					
						
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										 |  |  | fg = NonlinearFactorGraph; | 
					
						
							|  |  |  | fg.add(NonlinearEqualityPose2(0, p0)); | 
					
						
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										 |  |  | delta = p0.between(p1); | 
					
						
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										 |  |  | 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)); | 
					
						
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							|  |  |  | %% Create initial config | 
					
						
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										 |  |  | initial = Values; | 
					
						
							|  |  |  | initial.insert(0, p0); | 
					
						
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										 |  |  | initial.insert(1, hexagon.atPose2(1).retract([-0.1, 0.1,-0.1]')); | 
					
						
							|  |  |  | initial.insert(2, hexagon.atPose2(2).retract([ 0.1,-0.1, 0.1]')); | 
					
						
							|  |  |  | initial.insert(3, hexagon.atPose2(3).retract([-0.1, 0.1,-0.1]')); | 
					
						
							|  |  |  | initial.insert(4, hexagon.atPose2(4).retract([ 0.1,-0.1, 0.1]')); | 
					
						
							|  |  |  | initial.insert(5, hexagon.atPose2(5).retract([-0.1, 0.1,-0.1]')); | 
					
						
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							|  |  |  | %% Plot Initial Estimate | 
					
						
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										 |  |  | cla | 
					
						
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										 |  |  | plot2DTrajectory(initial, 'g*-'); axis equal | 
					
						
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							|  |  |  | %% optimize | 
					
						
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										 |  |  | optimizer = DoglegOptimizer(fg, initial); | 
					
						
							|  |  |  | result = optimizer.optimizeSafely; | 
					
						
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							|  |  |  | %% Show Result | 
					
						
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										 |  |  | hold on; plot2DTrajectory(result, 'b*-'); | 
					
						
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										 |  |  | view(2); | 
					
						
							|  |  |  | axis([-1.5 1.5 -1.5 1.5]); | 
					
						
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										 |  |  | result.print(sprintf('\nFinal result:\n')); |