99 lines
		
	
	
		
			3.2 KiB
		
	
	
	
		
			C++
		
	
	
			
		
		
	
	
			99 lines
		
	
	
		
			3.2 KiB
		
	
	
	
		
			C++
		
	
	
| /**
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|  * @file   NonlinearConjugateGradientOptimizer.cpp
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|  * @brief  Test simple CG optimizer
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|  * @author Yong-Dian Jian
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|  * @date   June 11, 2012
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|  */
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| 
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| /**
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|  * @file   testGradientDescentOptimizer.cpp
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|  * @brief  Small test of NonlinearConjugateGradientOptimizer
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|  * @author Yong-Dian Jian
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|  * @date   Jun 11, 2012
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|  */
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| 
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| #include <gtsam/slam/PriorFactor.h>
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| #include <gtsam/slam/BetweenFactor.h>
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| #include <gtsam/nonlinear/NonlinearConjugateGradientOptimizer.h>
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| #include <gtsam/nonlinear/NonlinearFactorGraph.h>
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| #include <gtsam/nonlinear/Values.h>
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| #include <gtsam/geometry/Pose2.h>
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| 
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| #include <CppUnitLite/TestHarness.h>
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| 
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| #include <boost/make_shared.hpp>
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| #include <boost/shared_ptr.hpp>
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| #include <boost/tuple/tuple.hpp>
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| 
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| using namespace std;
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| using namespace gtsam;
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| 
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| // Generate a small PoseSLAM problem
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| boost::tuple<NonlinearFactorGraph, Values> generateProblem() {
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| 
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|   // 1. Create graph container and add factors to it
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|   NonlinearFactorGraph graph;
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| 
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|   // 2a. Add Gaussian prior
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|   Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin
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|   SharedDiagonal priorNoise = noiseModel::Diagonal::Sigmas(
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|       Vector3(0.3, 0.3, 0.1));
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|   graph += PriorFactor<Pose2>(1, priorMean, priorNoise);
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| 
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|   // 2b. Add odometry factors
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|   SharedDiagonal odometryNoise = noiseModel::Diagonal::Sigmas(
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|       Vector3(0.2, 0.2, 0.1));
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|   graph += BetweenFactor<Pose2>(1, 2, Pose2(2.0, 0.0, 0.0), odometryNoise);
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|   graph += BetweenFactor<Pose2>(2, 3, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
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|   graph += BetweenFactor<Pose2>(3, 4, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
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|   graph += BetweenFactor<Pose2>(4, 5, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
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| 
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|   // 2c. Add pose constraint
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|   SharedDiagonal constraintUncertainty = noiseModel::Diagonal::Sigmas(
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|       Vector3(0.2, 0.2, 0.1));
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|   graph += BetweenFactor<Pose2>(5, 2, Pose2(2.0, 0.0, M_PI_2),
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|       constraintUncertainty);
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| 
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|   // 3. Create the data structure to hold the initialEstimate estimate to the solution
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|   Values initialEstimate;
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|   Pose2 x1(0.5, 0.0, 0.2);
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|   initialEstimate.insert(1, x1);
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|   Pose2 x2(2.3, 0.1, -0.2);
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|   initialEstimate.insert(2, x2);
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|   Pose2 x3(4.1, 0.1, M_PI_2);
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|   initialEstimate.insert(3, x3);
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|   Pose2 x4(4.0, 2.0, M_PI);
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|   initialEstimate.insert(4, x4);
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|   Pose2 x5(2.1, 2.1, -M_PI_2);
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|   initialEstimate.insert(5, x5);
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| 
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|   return boost::tie(graph, initialEstimate);
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| }
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| 
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| /* ************************************************************************* */
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| TEST(NonlinearConjugateGradientOptimizer, Optimize) {
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| 
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|   NonlinearFactorGraph graph;
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|   Values initialEstimate;
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| 
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|   boost::tie(graph, initialEstimate) = generateProblem();
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| //  cout << "initial error = " << graph.error(initialEstimate) << endl;
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| 
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|   NonlinearOptimizerParams param;
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|   param.maxIterations = 500; /* requires a larger number of iterations to converge */
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|   param.verbosity = NonlinearOptimizerParams::SILENT;
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| 
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|   NonlinearConjugateGradientOptimizer optimizer(graph, initialEstimate, param);
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|   Values result = optimizer.optimize();
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| //  cout << "cg final error = " << graph.error(result) << endl;
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| 
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|   EXPECT_DOUBLES_EQUAL(0.0, graph.error(result), 1e-4);
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| }
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| 
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| /* ************************************************************************* */
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| int main() {
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|   TestResult tr;
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|   return TestRegistry::runAllTests(tr);
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| }
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| /* ************************************************************************* */
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