478 lines
21 KiB
C++
478 lines
21 KiB
C++
/**
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* @file testBetweenFactorEM.cpp
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* @brief Unit test for the BetweenFactorEM
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* @author Vadim Indelman
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*/
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#include <CppUnitLite/TestHarness.h>
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#include <gtsam_unstable/slam/BetweenFactorEM.h>
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#include <gtsam/geometry/Pose2.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/base/LieVector.h>
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#include <gtsam/base/numericalDerivative.h>
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#include <gtsam/slam/BetweenFactor.h>
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//#include <gtsam/nonlinear/NonlinearOptimizer.h>
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//#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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//#include <gtsam/linear/GaussianSequentialSolver.h>
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using namespace std;
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using namespace gtsam;
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/* ************************************************************************* */
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LieVector predictionError(const Pose2& p1, const Pose2& p2, const gtsam::Key& key1, const gtsam::Key& key2, const BetweenFactorEM<gtsam::Pose2>& factor){
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gtsam::Values values;
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values.insert(key1, p1);
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values.insert(key2, p2);
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// LieVector err = factor.whitenedError(values);
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// return err;
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return LieVector::Expmap(factor.whitenedError(values));
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}
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/* ************************************************************************* */
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LieVector predictionError_standard(const Pose2& p1, const Pose2& p2, const gtsam::Key& key1, const gtsam::Key& key2, const BetweenFactor<gtsam::Pose2>& factor){
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gtsam::Values values;
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values.insert(key1, p1);
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values.insert(key2, p2);
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// LieVector err = factor.whitenedError(values);
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// return err;
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return LieVector::Expmap(factor.whitenedError(values));
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}
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/* ************************************************************************* */
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TEST( BetweenFactorEM, ConstructorAndEquals)
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{
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gtsam::Key key1(1);
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gtsam::Key key2(2);
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gtsam::Pose2 p1(10.0, 15.0, 0.1);
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gtsam::Pose2 p2(15.0, 15.0, 0.3);
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gtsam::Pose2 noise(0.5, 0.4, 0.01);
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gtsam::Pose2 rel_pose_ideal = p1.between(p2);
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gtsam::Pose2 rel_pose_msr = rel_pose_ideal.compose(noise);
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SharedGaussian model_inlier(noiseModel::Diagonal::Sigmas(gtsam::Vector_(3, 0.5, 0.5, 0.05)));
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SharedGaussian model_outlier(noiseModel::Diagonal::Sigmas(gtsam::Vector_(3, 5, 5, 1.0)));
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double prior_outlier = 0.5;
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double prior_inlier = 0.5;
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// Constructor
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BetweenFactorEM<gtsam::Pose2> f(key1, key2, rel_pose_msr, model_inlier, model_outlier,
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prior_inlier, prior_outlier);
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BetweenFactorEM<gtsam::Pose2> g(key1, key2, rel_pose_msr, model_inlier, model_outlier,
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prior_inlier, prior_outlier);
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// Equals
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CHECK(assert_equal(f, g, 1e-5));
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}
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/* ************************************************************************* */
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TEST( BetweenFactorEM, EvaluateError)
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{
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gtsam::Key key1(1);
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gtsam::Key key2(2);
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// Inlier test
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gtsam::Pose2 p1(10.0, 15.0, 0.1);
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gtsam::Pose2 p2(15.0, 15.0, 0.3);
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gtsam::Pose2 noise(0.5, 0.4, 0.01);
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gtsam::Pose2 rel_pose_ideal = p1.between(p2);
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gtsam::Pose2 rel_pose_msr = rel_pose_ideal.compose(noise);
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SharedGaussian model_inlier(noiseModel::Diagonal::Sigmas(gtsam::Vector_(3, 0.5, 0.5, 0.05)));
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SharedGaussian model_outlier(noiseModel::Diagonal::Sigmas(gtsam::Vector_(3, 50.0, 50.0, 10.0)));
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gtsam::Values values;
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values.insert(key1, p1);
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values.insert(key2, p2);
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double prior_outlier = 0.5;
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double prior_inlier = 0.5;
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BetweenFactorEM<gtsam::Pose2> f(key1, key2, rel_pose_msr, model_inlier, model_outlier,
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prior_inlier, prior_outlier);
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Vector actual_err_wh = f.whitenedError(values);
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Vector actual_err_wh_inlier = Vector_(3, actual_err_wh[0], actual_err_wh[1], actual_err_wh[2]);
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Vector actual_err_wh_outlier = Vector_(3, actual_err_wh[3], actual_err_wh[4], actual_err_wh[5]);
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// in case of inlier, inlier-mode whitented error should be dominant
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CHECK(actual_err_wh_inlier.norm() > 1000.0*actual_err_wh_outlier.norm());
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cout << "Inlier test. norm of actual_err_wh_inlier, actual_err_wh_outlier: "<<actual_err_wh_inlier.norm()<<","<<actual_err_wh_outlier.norm()<<endl;
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cout<<actual_err_wh[0]<<" "<<actual_err_wh[1]<<" "<<actual_err_wh[2]<<actual_err_wh[3]<<" "<<actual_err_wh[4]<<" "<<actual_err_wh[5]<<endl;
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// Outlier test
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noise = gtsam::Pose2(10.5, 20.4, 2.01);
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gtsam::Pose2 rel_pose_msr_test2 = rel_pose_ideal.compose(noise);
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BetweenFactorEM<gtsam::Pose2> g(key1, key2, rel_pose_msr_test2, model_inlier, model_outlier,
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prior_inlier, prior_outlier);
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actual_err_wh = g.whitenedError(values);
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actual_err_wh_inlier = Vector_(3, actual_err_wh[0], actual_err_wh[1], actual_err_wh[2]);
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actual_err_wh_outlier = Vector_(3, actual_err_wh[3], actual_err_wh[4], actual_err_wh[5]);
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// in case of outlier, outlier-mode whitented error should be dominant
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CHECK(actual_err_wh_inlier.norm() < 1000.0*actual_err_wh_outlier.norm());
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cout << "Outlier test. norm of actual_err_wh_inlier, actual_err_wh_outlier: "<<actual_err_wh_inlier.norm()<<","<<actual_err_wh_outlier<<endl;
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cout<<actual_err_wh[0]<<" "<<actual_err_wh[1]<<" "<<actual_err_wh[2]<<actual_err_wh[3]<<" "<<actual_err_wh[4]<<" "<<actual_err_wh[5]<<endl;
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// Compare with standard between factor for the inlier case
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prior_outlier = 0.0;
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prior_inlier = 1.0;
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BetweenFactorEM<gtsam::Pose2> h_EM(key1, key2, rel_pose_msr, model_inlier, model_outlier,
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prior_inlier, prior_outlier);
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actual_err_wh = h_EM.whitenedError(values);
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actual_err_wh_inlier = Vector_(3, actual_err_wh[0], actual_err_wh[1], actual_err_wh[2]);
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BetweenFactor<gtsam::Pose2> h(key1, key2, rel_pose_msr, model_inlier );
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Vector actual_err_wh_stnd = h.whitenedError(values);
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cout<<"actual_err_wh: "<<actual_err_wh_inlier[0]<<", "<<actual_err_wh_inlier[1]<<", "<<actual_err_wh_inlier[2]<<endl;
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cout<<"actual_err_wh_stnd: "<<actual_err_wh_stnd[0]<<", "<<actual_err_wh_stnd[1]<<", "<<actual_err_wh_stnd[2]<<endl;
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CHECK( assert_equal(actual_err_wh_inlier, actual_err_wh_stnd, 1e-8));
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}
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///* ************************************************************************** */
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TEST (BetweenFactorEM, jacobian ) {
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gtsam::Key key1(1);
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gtsam::Key key2(2);
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// Inlier test
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gtsam::Pose2 p1(10.0, 15.0, 0.1);
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gtsam::Pose2 p2(15.0, 15.0, 0.3);
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gtsam::Pose2 noise(0.5, 0.4, 0.01);
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gtsam::Pose2 rel_pose_ideal = p1.between(p2);
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gtsam::Pose2 rel_pose_msr = rel_pose_ideal.compose(noise);
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SharedGaussian model_inlier(noiseModel::Diagonal::Sigmas(gtsam::Vector_(3, 0.5, 0.5, 0.05)));
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SharedGaussian model_outlier(noiseModel::Diagonal::Sigmas(gtsam::Vector_(3, 50.0, 50.0, 10.0)));
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gtsam::Values values;
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values.insert(key1, p1);
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values.insert(key2, p2);
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double prior_outlier = 0.0;
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double prior_inlier = 1.0;
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BetweenFactorEM<gtsam::Pose2> f(key1, key2, rel_pose_msr, model_inlier, model_outlier,
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prior_inlier, prior_outlier);
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std::vector<gtsam::Matrix> H_actual(2);
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Vector actual_err_wh = f.whitenedError(values, H_actual);
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Matrix H1_actual = H_actual[0];
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Matrix H2_actual = H_actual[1];
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// compare to standard between factor
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BetweenFactor<gtsam::Pose2> h(key1, key2, rel_pose_msr, model_inlier );
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Vector actual_err_wh_stnd = h.whitenedError(values);
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Vector actual_err_wh_inlier = Vector_(3, actual_err_wh[0], actual_err_wh[1], actual_err_wh[2]);
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CHECK( assert_equal(actual_err_wh_stnd, actual_err_wh_inlier, 1e-8));
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std::vector<gtsam::Matrix> H_actual_stnd_unwh(2);
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(void)h.unwhitenedError(values, H_actual_stnd_unwh);
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Matrix H1_actual_stnd_unwh = H_actual_stnd_unwh[0];
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Matrix H2_actual_stnd_unwh = H_actual_stnd_unwh[1];
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Matrix H1_actual_stnd = model_inlier->Whiten(H1_actual_stnd_unwh);
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Matrix H2_actual_stnd = model_inlier->Whiten(H2_actual_stnd_unwh);
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// CHECK( assert_equal(H1_actual_stnd, H1_actual, 1e-8));
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// CHECK( assert_equal(H2_actual_stnd, H2_actual, 1e-8));
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double stepsize = 1.0e-9;
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Matrix H1_expected = gtsam::numericalDerivative11<LieVector, Pose2>(boost::bind(&predictionError, _1, p2, key1, key2, f), p1, stepsize);
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Matrix H2_expected = gtsam::numericalDerivative11<LieVector, Pose2>(boost::bind(&predictionError, p1, _1, key1, key2, f), p2, stepsize);
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// try to check numerical derivatives of a standard between factor
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Matrix H1_expected_stnd = gtsam::numericalDerivative11<LieVector, Pose2>(boost::bind(&predictionError_standard, _1, p2, key1, key2, h), p1, stepsize);
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CHECK( assert_equal(H1_expected_stnd, H1_actual_stnd, 1e-5));
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CHECK( assert_equal(H1_expected, H1_actual, 1e-8));
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CHECK( assert_equal(H2_expected, H2_actual, 1e-8));
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}
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/* ************************************************************************* */
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TEST( InertialNavFactor, Equals)
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{
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// gtsam::Key Pose1(11);
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// gtsam::Key Pose2(12);
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// gtsam::Key Vel1(21);
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// gtsam::Key Vel2(22);
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// gtsam::Key Bias1(31);
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//
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// Vector measurement_acc(Vector_(3,0.1,0.2,0.4));
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// Vector measurement_gyro(Vector_(3, -0.2, 0.5, 0.03));
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//
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// double measurement_dt(0.1);
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// Vector world_g(Vector_(3, 0.0, 0.0, 9.81));
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// Vector world_rho(Vector_(3, 0.0, -1.5724e-05, 0.0)); // NED system
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// gtsam::Vector ECEF_omega_earth(Vector_(3, 0.0, 0.0, 7.292115e-5));
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// gtsam::Vector world_omega_earth(world_R_ECEF.matrix() * ECEF_omega_earth);
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//
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// SharedGaussian model(noiseModel::Isotropic::Sigma(9, 0.1));
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//
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// InertialNavFactor<Pose3, LieVector, imuBias::ConstantBias> f(Pose1, Vel1, Bias1, Pose2, Vel2, measurement_acc, measurement_gyro, measurement_dt, world_g, world_rho, world_omega_earth, model);
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// InertialNavFactor<Pose3, LieVector, imuBias::ConstantBias> g(Pose1, Vel1, Bias1, Pose2, Vel2, measurement_acc, measurement_gyro, measurement_dt, world_g, world_rho, world_omega_earth, model);
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// CHECK(assert_equal(f, g, 1e-5));
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}
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/* ************************************************************************* */
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TEST( InertialNavFactor, Predict)
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{
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// gtsam::Key PoseKey1(11);
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// gtsam::Key PoseKey2(12);
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// gtsam::Key VelKey1(21);
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// gtsam::Key VelKey2(22);
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// gtsam::Key BiasKey1(31);
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//
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// double measurement_dt(0.1);
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// Vector world_g(Vector_(3, 0.0, 0.0, 9.81));
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// Vector world_rho(Vector_(3, 0.0, -1.5724e-05, 0.0)); // NED system
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// gtsam::Vector ECEF_omega_earth(Vector_(3, 0.0, 0.0, 7.292115e-5));
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// gtsam::Vector world_omega_earth(world_R_ECEF.matrix() * ECEF_omega_earth);
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//
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// SharedGaussian model(noiseModel::Isotropic::Sigma(9, 0.1));
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//
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//
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// // First test: zero angular motion, some acceleration
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// Vector measurement_acc(Vector_(3,0.1,0.2,0.3-9.81));
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// Vector measurement_gyro(Vector_(3, 0.0, 0.0, 0.0));
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//
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// InertialNavFactor<Pose3, LieVector, imuBias::ConstantBias> f(PoseKey1, VelKey1, BiasKey1, PoseKey2, VelKey2, measurement_acc, measurement_gyro, measurement_dt, world_g, world_rho, world_omega_earth, model);
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//
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// Pose3 Pose1(Rot3(), Point3(2.00, 1.00, 3.00));
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// LieVector Vel1(3, 0.50, -0.50, 0.40);
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// imuBias::ConstantBias Bias1;
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// Pose3 expectedPose2(Rot3(), Point3(2.05, 0.95, 3.04));
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// LieVector expectedVel2(3, 0.51, -0.48, 0.43);
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// Pose3 actualPose2;
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// LieVector actualVel2;
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// f.predict(Pose1, Vel1, Bias1, actualPose2, actualVel2);
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//
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// CHECK(assert_equal(expectedPose2, actualPose2, 1e-5));
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// CHECK(assert_equal(expectedVel2, actualVel2, 1e-5));
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}
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/* ************************************************************************* */
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TEST( InertialNavFactor, ErrorPosVel)
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{
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// gtsam::Key PoseKey1(11);
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// gtsam::Key PoseKey2(12);
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// gtsam::Key VelKey1(21);
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// gtsam::Key VelKey2(22);
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// gtsam::Key BiasKey1(31);
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//
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// double measurement_dt(0.1);
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// Vector world_g(Vector_(3, 0.0, 0.0, 9.81));
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// Vector world_rho(Vector_(3, 0.0, -1.5724e-05, 0.0)); // NED system
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// gtsam::Vector ECEF_omega_earth(Vector_(3, 0.0, 0.0, 7.292115e-5));
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// gtsam::Vector world_omega_earth(world_R_ECEF.matrix() * ECEF_omega_earth);
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//
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// SharedGaussian model(noiseModel::Isotropic::Sigma(9, 0.1));
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//
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//
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// // First test: zero angular motion, some acceleration
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// Vector measurement_acc(Vector_(3,0.1,0.2,0.3-9.81));
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// Vector measurement_gyro(Vector_(3, 0.0, 0.0, 0.0));
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//
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// InertialNavFactor<Pose3, LieVector, imuBias::ConstantBias> f(PoseKey1, VelKey1, BiasKey1, PoseKey2, VelKey2, measurement_acc, measurement_gyro, measurement_dt, world_g, world_rho, world_omega_earth, model);
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//
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// Pose3 Pose1(Rot3(), Point3(2.00, 1.00, 3.00));
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// Pose3 Pose2(Rot3(), Point3(2.05, 0.95, 3.04));
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// LieVector Vel1(3, 0.50, -0.50, 0.40);
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// LieVector Vel2(3, 0.51, -0.48, 0.43);
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// imuBias::ConstantBias Bias1;
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//
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// Vector ActualErr(f.evaluateError(Pose1, Vel1, Bias1, Pose2, Vel2));
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// Vector ExpectedErr(zero(9));
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//
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// CHECK(assert_equal(ExpectedErr, ActualErr, 1e-5));
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}
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/* ************************************************************************* */
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TEST( InertialNavFactor, ErrorRot)
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{
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// gtsam::Key PoseKey1(11);
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// gtsam::Key PoseKey2(12);
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// gtsam::Key VelKey1(21);
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// gtsam::Key VelKey2(22);
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// gtsam::Key BiasKey1(31);
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//
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// double measurement_dt(0.1);
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// Vector world_g(Vector_(3, 0.0, 0.0, 9.81));
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// Vector world_rho(Vector_(3, 0.0, -1.5724e-05, 0.0)); // NED system
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// gtsam::Vector ECEF_omega_earth(Vector_(3, 0.0, 0.0, 7.292115e-5));
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// gtsam::Vector world_omega_earth(world_R_ECEF.matrix() * ECEF_omega_earth);
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//
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// SharedGaussian model(noiseModel::Isotropic::Sigma(9, 0.1));
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//
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// // Second test: zero angular motion, some acceleration
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// Vector measurement_acc(Vector_(3,0.0,0.0,0.0-9.81));
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// Vector measurement_gyro(Vector_(3, 0.1, 0.2, 0.3));
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//
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// InertialNavFactor<Pose3, LieVector, imuBias::ConstantBias> f(PoseKey1, VelKey1, BiasKey1, PoseKey2, VelKey2, measurement_acc, measurement_gyro, measurement_dt, world_g, world_rho, world_omega_earth, model);
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//
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// Pose3 Pose1(Rot3(), Point3(2.0,1.0,3.0));
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// Pose3 Pose2(Rot3::Expmap(measurement_gyro*measurement_dt), Point3(2.0,1.0,3.0));
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// LieVector Vel1(3,0.0,0.0,0.0);
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// LieVector Vel2(3,0.0,0.0,0.0);
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// imuBias::ConstantBias Bias1;
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//
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// Vector ActualErr(f.evaluateError(Pose1, Vel1, Bias1, Pose2, Vel2));
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// Vector ExpectedErr(zero(9));
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//
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// CHECK(assert_equal(ExpectedErr, ActualErr, 1e-5));
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}
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/* ************************************************************************* */
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TEST( InertialNavFactor, ErrorRotPosVel)
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{
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// gtsam::Key PoseKey1(11);
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// gtsam::Key PoseKey2(12);
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// gtsam::Key VelKey1(21);
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// gtsam::Key VelKey2(22);
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// gtsam::Key BiasKey1(31);
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//
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// double measurement_dt(0.1);
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// Vector world_g(Vector_(3, 0.0, 0.0, 9.81));
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// Vector world_rho(Vector_(3, 0.0, -1.5724e-05, 0.0)); // NED system
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// gtsam::Vector ECEF_omega_earth(Vector_(3, 0.0, 0.0, 7.292115e-5));
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// gtsam::Vector world_omega_earth(world_R_ECEF.matrix() * ECEF_omega_earth);
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//
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// SharedGaussian model(noiseModel::Isotropic::Sigma(9, 0.1));
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//
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// // Second test: zero angular motion, some acceleration - generated in matlab
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// Vector measurement_acc(Vector_(3, 6.501390843381716, -6.763926150509185, -2.300389940090343));
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// Vector measurement_gyro(Vector_(3, 0.1, 0.2, 0.3));
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//
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// InertialNavFactor<Pose3, LieVector, imuBias::ConstantBias> f(PoseKey1, VelKey1, BiasKey1, PoseKey2, VelKey2, measurement_acc, measurement_gyro, measurement_dt, world_g, world_rho, world_omega_earth, model);
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//
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// Rot3 R1(0.487316618, 0.125253866, 0.86419557,
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// 0.580273724, 0.693095498, -0.427669306,
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// -0.652537293, 0.709880342, 0.265075427);
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// Point3 t1(2.0,1.0,3.0);
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// Pose3 Pose1(R1, t1);
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// LieVector Vel1(3,0.5,-0.5,0.4);
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// Rot3 R2(0.473618898, 0.119523052, 0.872582019,
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// 0.609241153, 0.67099888, -0.422594037,
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// -0.636011287, 0.731761397, 0.244979388);
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// Point3 t2(2.052670960415706, 0.977252139079380, 2.942482135362800);
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// Pose3 Pose2(R2, t2);
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// LieVector Vel2(3,0.510000000000000, -0.480000000000000, 0.430000000000000);
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// imuBias::ConstantBias Bias1;
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//
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// Vector ActualErr(f.evaluateError(Pose1, Vel1, Bias1, Pose2, Vel2));
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// Vector ExpectedErr(zero(9));
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//
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// CHECK(assert_equal(ExpectedErr, ActualErr, 1e-5));
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}
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/* ************************************************************************* */
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TEST (InertialNavFactor, Jacobian ) {
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// gtsam::Key PoseKey1(11);
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// gtsam::Key PoseKey2(12);
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// gtsam::Key VelKey1(21);
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// gtsam::Key VelKey2(22);
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// gtsam::Key BiasKey1(31);
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//
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// double measurement_dt(0.01);
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// Vector world_g(Vector_(3, 0.0, 0.0, 9.81));
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// Vector world_rho(Vector_(3, 0.0, -1.5724e-05, 0.0)); // NED system
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// gtsam::Vector ECEF_omega_earth(Vector_(3, 0.0, 0.0, 7.292115e-5));
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// gtsam::Vector world_omega_earth(world_R_ECEF.matrix() * ECEF_omega_earth);
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//
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// SharedGaussian model(noiseModel::Isotropic::Sigma(9, 0.1));
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//
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// Vector measurement_acc(Vector_(3, 6.501390843381716, -6.763926150509185, -2.300389940090343));
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// Vector measurement_gyro(Vector_(3, 3.14, 3.14/2, -3.14));
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//
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// InertialNavFactor<Pose3, LieVector, imuBias::ConstantBias> factor(PoseKey1, VelKey1, BiasKey1, PoseKey2, VelKey2, measurement_acc, measurement_gyro, measurement_dt, world_g, world_rho, world_omega_earth, model);
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//
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// Rot3 R1(0.487316618, 0.125253866, 0.86419557,
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// 0.580273724, 0.693095498, -0.427669306,
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// -0.652537293, 0.709880342, 0.265075427);
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// Point3 t1(2.0,1.0,3.0);
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// Pose3 Pose1(R1, t1);
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// LieVector Vel1(3,0.5,-0.5,0.4);
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// Rot3 R2(0.473618898, 0.119523052, 0.872582019,
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// 0.609241153, 0.67099888, -0.422594037,
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// -0.636011287, 0.731761397, 0.244979388);
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// Point3 t2(2.052670960415706, 0.977252139079380, 2.942482135362800);
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// Pose3 Pose2(R2, t2);
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// LieVector Vel2(3,0.510000000000000, -0.480000000000000, 0.430000000000000);
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// imuBias::ConstantBias Bias1;
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//
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// Matrix H1_actual, H2_actual, H3_actual, H4_actual, H5_actual;
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//
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// Vector ActualErr(factor.evaluateError(Pose1, Vel1, Bias1, Pose2, Vel2, H1_actual, H2_actual, H3_actual, H4_actual, H5_actual));
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//
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// // Checking for Pose part in the jacobians
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// // ******
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// Matrix H1_actualPose(H1_actual.block(0,0,6,H1_actual.cols()));
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// Matrix H2_actualPose(H2_actual.block(0,0,6,H2_actual.cols()));
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// Matrix H3_actualPose(H3_actual.block(0,0,6,H3_actual.cols()));
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// Matrix H4_actualPose(H4_actual.block(0,0,6,H4_actual.cols()));
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// Matrix H5_actualPose(H5_actual.block(0,0,6,H5_actual.cols()));
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//
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// // Calculate the Jacobian matrices H1 until H5 using the numerical derivative function
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// gtsam::Matrix H1_expectedPose, H2_expectedPose, H3_expectedPose, H4_expectedPose, H5_expectedPose;
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// H1_expectedPose = gtsam::numericalDerivative11<Pose3, Pose3>(boost::bind(&predictionErrorPose, _1, Vel1, Bias1, Pose2, Vel2, factor), Pose1);
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// H2_expectedPose = gtsam::numericalDerivative11<Pose3, LieVector>(boost::bind(&predictionErrorPose, Pose1, _1, Bias1, Pose2, Vel2, factor), Vel1);
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// H3_expectedPose = gtsam::numericalDerivative11<Pose3, imuBias::ConstantBias>(boost::bind(&predictionErrorPose, Pose1, Vel1, _1, Pose2, Vel2, factor), Bias1);
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// H4_expectedPose = gtsam::numericalDerivative11<Pose3, Pose3>(boost::bind(&predictionErrorPose, Pose1, Vel1, Bias1, _1, Vel2, factor), Pose2);
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// H5_expectedPose = gtsam::numericalDerivative11<Pose3, LieVector>(boost::bind(&predictionErrorPose, Pose1, Vel1, Bias1, Pose2, _1, factor), Vel2);
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//
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// // Verify they are equal for this choice of state
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// CHECK( gtsam::assert_equal(H1_expectedPose, H1_actualPose, 1e-6));
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// CHECK( gtsam::assert_equal(H2_expectedPose, H2_actualPose, 1e-6));
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// CHECK( gtsam::assert_equal(H3_expectedPose, H3_actualPose, 1e-6));
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// CHECK( gtsam::assert_equal(H4_expectedPose, H4_actualPose, 1e-6));
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// CHECK( gtsam::assert_equal(H5_expectedPose, H5_actualPose, 1e-6));
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//
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// // Checking for Vel part in the jacobians
|
|
// // ******
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|
// Matrix H1_actualVel(H1_actual.block(6,0,3,H1_actual.cols()));
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|
// Matrix H2_actualVel(H2_actual.block(6,0,3,H2_actual.cols()));
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|
// Matrix H3_actualVel(H3_actual.block(6,0,3,H3_actual.cols()));
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|
// Matrix H4_actualVel(H4_actual.block(6,0,3,H4_actual.cols()));
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|
// Matrix H5_actualVel(H5_actual.block(6,0,3,H5_actual.cols()));
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|
//
|
|
// // Calculate the Jacobian matrices H1 until H5 using the numerical derivative function
|
|
// gtsam::Matrix H1_expectedVel, H2_expectedVel, H3_expectedVel, H4_expectedVel, H5_expectedVel;
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|
// H1_expectedVel = gtsam::numericalDerivative11<LieVector, Pose3>(boost::bind(&predictionErrorVel, _1, Vel1, Bias1, Pose2, Vel2, factor), Pose1);
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|
// H2_expectedVel = gtsam::numericalDerivative11<LieVector, LieVector>(boost::bind(&predictionErrorVel, Pose1, _1, Bias1, Pose2, Vel2, factor), Vel1);
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|
// H3_expectedVel = gtsam::numericalDerivative11<LieVector, imuBias::ConstantBias>(boost::bind(&predictionErrorVel, Pose1, Vel1, _1, Pose2, Vel2, factor), Bias1);
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|
// H4_expectedVel = gtsam::numericalDerivative11<LieVector, Pose3>(boost::bind(&predictionErrorVel, Pose1, Vel1, Bias1, _1, Vel2, factor), Pose2);
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|
// H5_expectedVel = gtsam::numericalDerivative11<LieVector, LieVector>(boost::bind(&predictionErrorVel, Pose1, Vel1, Bias1, Pose2, _1, factor), Vel2);
|
|
//
|
|
// // Verify they are equal for this choice of state
|
|
// CHECK( gtsam::assert_equal(H1_expectedVel, H1_actualVel, 1e-6));
|
|
// CHECK( gtsam::assert_equal(H2_expectedVel, H2_actualVel, 1e-6));
|
|
// CHECK( gtsam::assert_equal(H3_expectedVel, H3_actualVel, 1e-6));
|
|
// CHECK( gtsam::assert_equal(H4_expectedVel, H4_actualVel, 1e-6));
|
|
// CHECK( gtsam::assert_equal(H5_expectedVel, H5_actualVel, 1e-6));
|
|
}
|
|
|
|
|
|
|
|
/* ************************************************************************* */
|
|
int main() { TestResult tr; return TestRegistry::runAllTests(tr);}
|
|
/* ************************************************************************* */
|