131 lines
4.6 KiB
C++
131 lines
4.6 KiB
C++
/**
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* @file testGradientDescentOptimizer.cpp
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* @brief
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* @author ydjian
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* @date Jun 11, 2012
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*/
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#include <gtsam/slam/pose2SLAM.h>
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#include <gtsam/nonlinear/GradientDescentOptimizer.h>
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#include <CppUnitLite/TestHarness.h>
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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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using namespace std;
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using namespace gtsam;
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boost::tuple<pose2SLAM::Graph, Values> generateProblem() {
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// 1. Create graph container and add factors to it
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pose2SLAM::Graph graph ;
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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(Vector_(3, 0.3, 0.3, 0.1));
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graph.addPosePrior(1, priorMean, priorNoise);
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// 2b. Add odometry factors
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SharedDiagonal odometryNoise = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1));
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graph.addRelativePose(1, 2, Pose2(2.0, 0.0, 0.0 ), odometryNoise);
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graph.addRelativePose(2, 3, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
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graph.addRelativePose(3, 4, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
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graph.addRelativePose(4, 5, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
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// 2c. Add pose constraint
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SharedDiagonal constraintUncertainty = noiseModel::Diagonal::Sigmas(Vector_(3, 0.2, 0.2, 0.1));
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graph.addRelativePose(5, 2, Pose2(2.0, 0.0, M_PI_2), constraintUncertainty);
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// 3. Create the data structure to hold the initialEstimate estinmate to the solution
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pose2SLAM::Values initialEstimate;
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Pose2 x1(0.5, 0.0, 0.2 ); initialEstimate.insertPose(1, x1);
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Pose2 x2(2.3, 0.1,-0.2 ); initialEstimate.insertPose(2, x2);
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Pose2 x3(4.1, 0.1, M_PI_2); initialEstimate.insertPose(3, x3);
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Pose2 x4(4.0, 2.0, M_PI ); initialEstimate.insertPose(4, x4);
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Pose2 x5(2.1, 2.1,-M_PI_2); initialEstimate.insertPose(5, x5);
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return boost::tie(graph, initialEstimate);
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}
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/* ************************************************************************* */
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TEST(optimize, GradientDescentOptimizer) {
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pose2SLAM::Graph graph ;
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pose2SLAM::Values initialEstimate;
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boost::tie(graph, initialEstimate) = generateProblem();
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// cout << "initial error = " << graph.error(initialEstimate) << endl ;
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// Single Step Optimization using Levenberg-Marquardt
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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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GradientDescentOptimizer optimizer(graph, initialEstimate, param);
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Values result = optimizer.optimize();
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// cout << "gd1 solver final error = " << graph.error(result) << endl;
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/* the optimality of the solution is not comparable to the */
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DOUBLES_EQUAL(0.0, graph.error(result), 1e-2);
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CHECK(1);
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}
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/* ************************************************************************* */
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TEST(optimize, ConjugateGradientOptimizer) {
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pose2SLAM::Graph graph ;
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pose2SLAM::Values initialEstimate;
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boost::tie(graph, initialEstimate) = generateProblem();
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// cout << "initial error = " << graph.error(initialEstimate) << endl ;
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// Single Step Optimization using Levenberg-Marquardt
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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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ConjugateGradientOptimizer optimizer(graph, initialEstimate, param, true);
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Values result = optimizer.optimize();
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// cout << "cg final error = " << graph.error(result) << endl;
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/* the optimality of the solution is not comparable to the */
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DOUBLES_EQUAL(0.0, graph.error(result), 1e-2);
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}
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/* ************************************************************************* */
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TEST(optimize, GradientDescentOptimizer2) {
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pose2SLAM::Graph graph ;
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pose2SLAM::Values initialEstimate;
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boost::tie(graph, initialEstimate) = generateProblem();
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// cout << "initial error = " << graph.error(initialEstimate) << endl ;
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// Single Step Optimization using Levenberg-Marquardt
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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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ConjugateGradientOptimizer optimizer(graph, initialEstimate, param, false);
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Values result = optimizer.optimize();
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// cout << "gd2 solver final error = " << graph.error(result) << endl;
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/* the optimality of the solution is not comparable to the */
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DOUBLES_EQUAL(0.0, graph.error(result), 1e-2);
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}
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/* ************************************************************************* */
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int main() { TestResult tr; return TestRegistry::runAllTests(tr); }
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/* ************************************************************************* */
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