302 lines
11 KiB
C++
302 lines
11 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/numericalDerivative.h>
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#include <gtsam/slam/BetweenFactor.h>
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using namespace std;
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using namespace gtsam;
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// Disabled this test because it is currently failing - remove the lines "#if 0" and "#endif" below
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// to reenable the test.
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#if 0
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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::Vector3(0.5, 0.5, 0.05)));
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SharedGaussian model_outlier(noiseModel::Diagonal::Sigmas(gtsam::Vector3(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::Vector3(0.5, 0.5, 0.05)));
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SharedGaussian model_outlier(noiseModel::Diagonal::Sigmas(gtsam::Vector3(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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// 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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// 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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// 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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//
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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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//
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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::Vector3(0.5, 0.5, 0.05)));
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SharedGaussian model_outlier(noiseModel::Diagonal::Sigmas(gtsam::Vector3(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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//
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//
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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( BetweenFactorEM, CaseStudy)
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{
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bool debug = false;
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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;
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gtsam::Pose2 p2(-0.0491752554, -0.289649075, -0.328993962);
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gtsam::Pose2 rel_pose_msr(0.0316191379, 0.0247539161, 0.004102182);
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SharedGaussian model_inlier(noiseModel::Diagonal::Sigmas(gtsam::Vector3(0.4021, 0.286, 0.428)));
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SharedGaussian model_outlier(noiseModel::Diagonal::Sigmas(gtsam::Vector3(4.9821, 4.614, 1.8387)));
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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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if (debug)
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cout << "==== inside CaseStudy ===="<<endl;
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gtsam::Vector p_inlier_outler = f.calcIndicatorProb(values);
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Vector actual_err_unw = f.unwhitenedError(values);
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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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if (debug){
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cout << "p_inlier_outler: "<<p_inlier_outler[0]<<", "<<p_inlier_outler[1]<<endl;
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cout<<"actual_err_unw: "<<actual_err_unw[0]<<", "<<actual_err_unw[1]<<", "<<actual_err_unw[2]<<endl;
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cout<<"actual_err_wh_inlier: "<<actual_err_wh_inlier[0]<<", "<<actual_err_wh_inlier[1]<<", "<<actual_err_wh_inlier[2]<<endl;
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cout<<"actual_err_wh_outlier: "<<actual_err_wh_outlier[0]<<", "<<actual_err_wh_outlier[1]<<", "<<actual_err_wh_outlier[2]<<endl;
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}
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}
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///* ************************************************************************** */
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TEST (BetweenFactorEM, updateNoiseModel ) {
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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) << 1.5, 2.5, 4.05)));
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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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SharedGaussian model = SharedGaussian(noiseModel::Isotropic::Sigma(3, 1e2));
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NonlinearFactorGraph graph;
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graph.addPrior(key1, p1, model);
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graph.addPrior(key2, p2, model);
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f.updateNoiseModels(values, graph);
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SharedGaussian model_inlier_new = f.get_model_inlier();
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SharedGaussian model_outlier_new = f.get_model_outlier();
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model_inlier->print("model_inlier:");
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model_outlier->print("model_outlier:");
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model_inlier_new->print("model_inlier_new:");
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model_outlier_new->print("model_outlier_new:");
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}
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#endif
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/* ************************************************************************* */
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int main() { TestResult tr; return TestRegistry::runAllTests(tr);}
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/* ************************************************************************* */
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