70 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			Matlab
		
	
	
		
		
			
		
	
	
			70 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			Matlab
		
	
	
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								% GTSAM Copyright 2010, Georgia Tech Research Corporation,
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								% Atlanta, Georgia 30332-0415
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								% All Rights Reserved
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								% Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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								%
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								% See LICENSE for the license information
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								%
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								% @brief Checks for serialization using basic string interface
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								% @author Alex Cunningham
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								% @author Frank Dellaert
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								%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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								import gtsam.*
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								%% Create keys for variables
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								i1 = symbol('x',1); i2 = symbol('x',2); i3 = symbol('x',3);
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								j1 = symbol('l',1); j2 = symbol('l',2);
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								%% Create values and verify string serialization
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								pose1=Pose2(0.5, 0.0, 0.2);
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								pose2=Pose2(2.3, 0.1,-0.2);
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								pose3=Pose2(4.1, 0.1, 0.1);
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								landmark1=Point2(1.8, 2.1);
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								landmark2=Point2(4.1, 1.8);
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								serialized_pose1 = pose1.string_serialize();
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								pose1ds = Pose2.string_deserialize(serialized_pose1);
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								CHECK('pose1ds.equals(pose1, 1e-9)', pose1ds.equals(pose1, 1e-9));
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								serialized_landmark1 = landmark1.string_serialize();
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								landmark1ds = Point2.string_deserialize(serialized_landmark1);
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								CHECK('landmark1ds.equals(landmark1, 1e-9)', landmark1ds.equals(landmark1, 1e-9));
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								%% Create and serialize Values
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								values = Values;
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								values.insert(i1, pose1);
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								values.insert(i2, pose2);
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								values.insert(i3, pose3);
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								values.insert(j1, landmark1);
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								values.insert(j2, landmark2);
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								serialized_values = values.string_serialize();
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								valuesds = Values.string_deserialize(serialized_values);
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								CHECK('valuesds.equals(values, 1e-9)', valuesds.equals(values, 1e-9));
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								%% Create graph and factors and serialize
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								graph = NonlinearFactorGraph;
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								% Prior factor
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								priorMean = Pose2(0.0, 0.0, 0.0); % prior at origin
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								priorNoise = noiseModel.Diagonal.Sigmas([0.3; 0.3; 0.1]);
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								graph.add(PriorFactorPose2(i1, priorMean, priorNoise)); % add directly to graph
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								% Between Factors - FAIL: unregistered class
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								odometry = Pose2(2.0, 0.0, 0.0);
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								odometryNoise = noiseModel.Diagonal.Sigmas([0.2; 0.2; 0.1]);
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								graph.add(BetweenFactorPose2(i1, i2, odometry, odometryNoise));
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								graph.add(BetweenFactorPose2(i2, i3, odometry, odometryNoise));
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								% BearingRange Factors - FAIL: unregistered class
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								degrees = pi/180;
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								brNoise = noiseModel.Diagonal.Sigmas([0.1; 0.2]);
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								graph.add(BearingRangeFactor2D(i1, j1, Rot2(45*degrees), sqrt(4+4), brNoise));
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								graph.add(BearingRangeFactor2D(i2, j1, Rot2(90*degrees), 2, brNoise));
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								graph.add(BearingRangeFactor2D(i3, j2, Rot2(90*degrees), 2, brNoise));
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								serialized_graph = graph.string_serialize();
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								graphds = NonlinearFactorGraph.string_deserialize(serialized_graph);
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								CHECK('graphds.equals(graph, 1e-9)', graphds.equals(graph, 1e-9));
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