872 lines
33 KiB
C++
872 lines
33 KiB
C++
/* ----------------------------------------------------------------------------
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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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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file testSmartProjectionPoseFactorRollingShutterRollingShutter.cpp
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* @brief Unit tests for SmartProjectionPoseFactorRollingShutterRollingShutter Class
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* @author Luca Carlone
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* @date July 2021
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*/
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#include "gtsam/slam/tests/smartFactorScenarios.h"
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#include <gtsam/slam/ProjectionFactor.h>
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#include <gtsam/slam/PoseTranslationPrior.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam_unstable/slam/SmartProjectionPoseFactorRollingShutter.h>
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#include <gtsam_unstable/slam/ProjectionFactorRollingShutter.h>
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#include <gtsam/base/numericalDerivative.h>
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#include <gtsam/base/serializationTestHelpers.h>
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#include <CppUnitLite/TestHarness.h>
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#include <boost/assign/std/map.hpp>
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#include <iostream>
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using namespace gtsam;
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using namespace boost::assign;
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using namespace std::placeholders;
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static const double rankTol = 1.0;
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// Create a noise model for the pixel error
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static const double sigma = 0.1;
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static SharedIsotropic model(noiseModel::Isotropic::Sigma(2, sigma));
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// Convenience for named keys
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using symbol_shorthand::X;
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using symbol_shorthand::L;
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// tests data
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static Symbol x1('X', 1);
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static Symbol x2('X', 2);
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static Symbol x3('X', 3);
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static Symbol x4('X', 4);
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static Symbol l0('L', 0);
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static Pose3 body_P_sensor = Pose3(Rot3::Ypr(-0.1, 0.2, -0.2),
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Point3(0.1, 0.0, 0.0));
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static Point2 measurement1(323.0, 240.0);
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static Point2 measurement2(200.0, 220.0);
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static Point2 measurement3(320.0, 10.0);
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static double interp_factor = 0.5;
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static double interp_factor1 = 0.3;
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static double interp_factor2 = 0.4;
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static double interp_factor3 = 0.5;
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/* ************************************************************************* */
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// default Cal3_S2 poses with rolling shutter effect
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namespace vanillaPoseRS {
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typedef PinholePose<Cal3_S2> Camera;
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static Cal3_S2::shared_ptr sharedK(new Cal3_S2(fov, w, h));
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Pose3 interp_pose1 = interpolate<Pose3>(level_pose,pose_right,interp_factor1);
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Pose3 interp_pose2 = interpolate<Pose3>(pose_right,pose_above,interp_factor2);
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Pose3 interp_pose3 = interpolate<Pose3>(pose_above,level_pose,interp_factor3);
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Camera cam1(interp_pose1, sharedK);
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Camera cam2(interp_pose2, sharedK);
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Camera cam3(interp_pose3, sharedK);
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}
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LevenbergMarquardtParams lmParams;
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typedef SmartProjectionPoseFactorRollingShutter<Cal3_S2> SmartFactorRS;
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/* ************************************************************************* */
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TEST( SmartProjectionPoseFactorRollingShutter, Constructor) {
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SmartFactorRS::shared_ptr factor1(new SmartFactorRS(model));
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}
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/* ************************************************************************* */
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TEST( SmartProjectionPoseFactorRollingShutter, Constructor2) {
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SmartProjectionParams params;
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params.setRankTolerance(rankTol);
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SmartFactorRS factor1(model, params);
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}
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/* ************************************************************************* */
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TEST( SmartProjectionPoseFactorRollingShutter, add) {
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using namespace vanillaPose;
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SmartFactorRS::shared_ptr factor1(new SmartFactorRS(model));
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factor1->add(measurement1, x1, x2, interp_factor, sharedK, body_P_sensor);
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}
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/* ************************************************************************* */
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TEST( SmartProjectionPoseFactorRollingShutter, Equals ) {
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using namespace vanillaPose;
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// create fake measurements
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std::vector<Point2> measurements;
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measurements.push_back(measurement1);
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measurements.push_back(measurement2);
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measurements.push_back(measurement3);
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std::vector<std::pair<Key,Key>> key_pairs;
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key_pairs.push_back(std::make_pair(x1,x2));
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key_pairs.push_back(std::make_pair(x2,x3));
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key_pairs.push_back(std::make_pair(x3,x4));
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std::vector<boost::shared_ptr<Cal3_S2>> intrinsicCalibrations;
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intrinsicCalibrations.push_back(sharedK);
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intrinsicCalibrations.push_back(sharedK);
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intrinsicCalibrations.push_back(sharedK);
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std::vector<Pose3> extrinsicCalibrations;
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extrinsicCalibrations.push_back(body_P_sensor);
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extrinsicCalibrations.push_back(body_P_sensor);
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extrinsicCalibrations.push_back(body_P_sensor);
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std::vector<double> interp_factors;
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interp_factors.push_back(interp_factor1);
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interp_factors.push_back(interp_factor2);
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interp_factors.push_back(interp_factor3);
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// create by adding a batch of measurements with a bunch of calibrations
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SmartFactorRS::shared_ptr factor2(new SmartFactorRS(model));
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factor2->add(measurements, key_pairs, interp_factors, intrinsicCalibrations, extrinsicCalibrations);
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// create by adding a batch of measurements with a single calibrations
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SmartFactorRS::shared_ptr factor3(new SmartFactorRS(model));
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factor3->add(measurements, key_pairs, interp_factors, sharedK, body_P_sensor);
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{ // create equal factors and show equal returns true
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SmartFactorRS::shared_ptr factor1(new SmartFactorRS(model));
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factor1->add(measurement1, x1, x2, interp_factor1, sharedK, body_P_sensor);
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factor1->add(measurement2, x2, x3, interp_factor2, sharedK, body_P_sensor);
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factor1->add(measurement3, x3, x4, interp_factor3, sharedK, body_P_sensor);
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CHECK(assert_equal(*factor1, *factor2));
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CHECK(assert_equal(*factor1, *factor3));
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}
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{ // create slightly different factors (different keys) and show equal returns false
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SmartFactorRS::shared_ptr factor1(new SmartFactorRS(model));
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factor1->add(measurement1, x1, x2, interp_factor1, sharedK, body_P_sensor);
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factor1->add(measurement2, x2, x2, interp_factor2, sharedK, body_P_sensor); // different!
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factor1->add(measurement3, x3, x4, interp_factor3, sharedK, body_P_sensor);
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CHECK(!assert_equal(*factor1, *factor2));
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CHECK(!assert_equal(*factor1, *factor3));
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}
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{ // create slightly different factors (different extrinsics) and show equal returns false
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SmartFactorRS::shared_ptr factor1(new SmartFactorRS(model));
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factor1->add(measurement1, x1, x2, interp_factor1, sharedK, body_P_sensor);
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factor1->add(measurement2, x2, x3, interp_factor2, sharedK, body_P_sensor*body_P_sensor); // different!
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factor1->add(measurement3, x3, x4, interp_factor3, sharedK, body_P_sensor);
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CHECK(!assert_equal(*factor1, *factor2));
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CHECK(!assert_equal(*factor1, *factor3));
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}
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{ // create slightly different factors (different interp factors) and show equal returns false
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SmartFactorRS::shared_ptr factor1(new SmartFactorRS(model));
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factor1->add(measurement1, x1, x2, interp_factor1, sharedK, body_P_sensor);
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factor1->add(measurement2, x2, x3, interp_factor1, sharedK, body_P_sensor); // different!
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factor1->add(measurement3, x3, x4, interp_factor3, sharedK, body_P_sensor);
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CHECK(!assert_equal(*factor1, *factor2));
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CHECK(!assert_equal(*factor1, *factor3));
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}
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}
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static const int DimBlock = 12; ///< size of the variable stacking 2 poses from which the observation pose is interpolated
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static const int DimPose = 6; ///< Pose3 dimension
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static const int ZDim = 2; ///< Measurement dimension (Point2)
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typedef Eigen::Matrix<double, ZDim, DimBlock> MatrixZD; // F blocks (derivatives wrt camera)
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typedef std::vector<MatrixZD, Eigen::aligned_allocator<MatrixZD> > FBlocks; // vector of F blocks
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/* *************************************************************************/
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TEST( SmartProjectionPoseFactorRollingShutter, noiselessErrorAndJacobians ) {
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using namespace vanillaPoseRS;
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// Project two landmarks into two cameras
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Point2 level_uv = cam1.project(landmark1);
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Point2 level_uv_right = cam2.project(landmark1);
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Pose3 body_P_sensorId = Pose3::identity();
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SmartFactorRS factor(model);
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factor.add(level_uv, x1, x2, interp_factor1, sharedK, body_P_sensorId);
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factor.add(level_uv_right, x2, x3, interp_factor2, sharedK, body_P_sensorId);
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Values values; // it's a pose factor, hence these are poses
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values.insert(x1, level_pose);
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values.insert(x2, pose_right);
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values.insert(x3, pose_above);
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double actualError = factor.error(values);
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double expectedError = 0.0;
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EXPECT_DOUBLES_EQUAL(expectedError, actualError, 1e-7);
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// Check triangulation
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factor.triangulateSafe(factor.cameras(values));
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TriangulationResult point = factor.point();
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CHECK(point.valid()); // check triangulated point is valid
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CHECK(assert_equal(landmark1, *point)); // check triangulation result matches expected 3D landmark
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// Check Jacobians
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// -- actual Jacobians
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FBlocks actualFs;
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Matrix actualE;
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Vector actualb;
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factor.computeJacobiansWithTriangulatedPoint(actualFs, actualE, actualb, values);
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CHECK(actualE.rows() == 4); CHECK(actualE.cols() == 3);
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CHECK(actualb.rows() == 4); CHECK(actualb.cols() == 1);
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CHECK(actualFs.size() == 2);
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// -- expected Jacobians from ProjectionFactorsRollingShutter
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ProjectionFactorRollingShutter factor1(level_uv, interp_factor1, model, x1, x2, l0, sharedK, body_P_sensorId);
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Matrix expectedF11, expectedF12, expectedE1;
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Vector expectedb1 = factor1.evaluateError(level_pose, pose_right, landmark1, expectedF11, expectedF12, expectedE1);
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CHECK(assert_equal( expectedF11, Matrix(actualFs[0].block(0,0,2,6)), 1e-5));
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CHECK(assert_equal( expectedF12, Matrix(actualFs[0].block(0,6,2,6)), 1e-5));
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CHECK(assert_equal( expectedE1, Matrix(actualE.block(0,0,2,3)), 1e-5));
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// by definition computeJacobiansWithTriangulatedPoint returns minus reprojectionError
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CHECK(assert_equal( expectedb1, -Vector(actualb.segment<2>(0)), 1e-5));
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ProjectionFactorRollingShutter factor2(level_uv_right, interp_factor2, model, x2, x3, l0, sharedK, body_P_sensorId);
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Matrix expectedF21, expectedF22, expectedE2;
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Vector expectedb2 = factor2.evaluateError(pose_right, pose_above, landmark1, expectedF21, expectedF22, expectedE2);
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CHECK(assert_equal( expectedF21, Matrix(actualFs[1].block(0,0,2,6)), 1e-5));
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CHECK(assert_equal( expectedF22, Matrix(actualFs[1].block(0,6,2,6)), 1e-5));
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CHECK(assert_equal( expectedE2, Matrix(actualE.block(2,0,2,3)), 1e-5));
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// by definition computeJacobiansWithTriangulatedPoint returns minus reprojectionError
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CHECK(assert_equal( expectedb2, -Vector(actualb.segment<2>(2)), 1e-5));
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}
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/* *************************************************************************/
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TEST( SmartProjectionPoseFactorRollingShutter, noisyErrorAndJacobians ) {
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// also includes non-identical extrinsic calibration
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using namespace vanillaPoseRS;
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// Project two landmarks into two cameras
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Point2 pixelError(0.5, 1.0);
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Point2 level_uv = cam1.project(landmark1) + pixelError;
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Point2 level_uv_right = cam2.project(landmark1);
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Pose3 body_P_sensorNonId = body_P_sensor;
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SmartFactorRS factor(model);
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factor.add(level_uv, x1, x2, interp_factor1, sharedK, body_P_sensorNonId);
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factor.add(level_uv_right, x2, x3, interp_factor2, sharedK, body_P_sensorNonId);
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Values values; // it's a pose factor, hence these are poses
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values.insert(x1, level_pose);
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values.insert(x2, pose_right);
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values.insert(x3, pose_above);
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// Perform triangulation
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factor.triangulateSafe(factor.cameras(values));
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TriangulationResult point = factor.point();
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CHECK(point.valid()); // check triangulated point is valid
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Point3 landmarkNoisy = *point;
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// Check Jacobians
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// -- actual Jacobians
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FBlocks actualFs;
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Matrix actualE;
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Vector actualb;
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factor.computeJacobiansWithTriangulatedPoint(actualFs, actualE, actualb, values);
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CHECK(actualE.rows() == 4); CHECK(actualE.cols() == 3);
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CHECK(actualb.rows() == 4); CHECK(actualb.cols() == 1);
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CHECK(actualFs.size() == 2);
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// -- expected Jacobians from ProjectionFactorsRollingShutter
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ProjectionFactorRollingShutter factor1(level_uv, interp_factor1, model, x1, x2, l0, sharedK, body_P_sensorNonId);
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Matrix expectedF11, expectedF12, expectedE1;
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Vector expectedb1 = factor1.evaluateError(level_pose, pose_right, landmarkNoisy, expectedF11, expectedF12, expectedE1);
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CHECK(assert_equal( expectedF11, Matrix(actualFs[0].block(0,0,2,6)), 1e-5));
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CHECK(assert_equal( expectedF12, Matrix(actualFs[0].block(0,6,2,6)), 1e-5));
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CHECK(assert_equal( expectedE1, Matrix(actualE.block(0,0,2,3)), 1e-5));
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// by definition computeJacobiansWithTriangulatedPoint returns minus reprojectionError
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CHECK(assert_equal( expectedb1, -Vector(actualb.segment<2>(0)), 1e-5));
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ProjectionFactorRollingShutter factor2(level_uv_right, interp_factor2, model, x2, x3, l0, sharedK, body_P_sensorNonId);
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Matrix expectedF21, expectedF22, expectedE2;
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Vector expectedb2 = factor2.evaluateError(pose_right, pose_above, landmarkNoisy, expectedF21, expectedF22, expectedE2);
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CHECK(assert_equal( expectedF21, Matrix(actualFs[1].block(0,0,2,6)), 1e-5));
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CHECK(assert_equal( expectedF22, Matrix(actualFs[1].block(0,6,2,6)), 1e-5));
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CHECK(assert_equal( expectedE2, Matrix(actualE.block(2,0,2,3)), 1e-5));
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// by definition computeJacobiansWithTriangulatedPoint returns minus reprojectionError
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CHECK(assert_equal( expectedb2, -Vector(actualb.segment<2>(2)), 1e-5));
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// Check errors
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double actualError = factor.error(values); // from smart factor
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NonlinearFactorGraph nfg;
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nfg.add(factor1);
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nfg.add(factor2);
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values.insert(l0, landmarkNoisy);
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double expectedError = nfg.error(values);
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EXPECT_DOUBLES_EQUAL(expectedError, actualError, 1e-7);
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}
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/* *************************************************************************
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TEST( SmartProjectionPoseFactorRollingShutter, 3poses_smart_projection_factor ) {
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using namespace vanillaPose2;
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Point2Vector measurements_cam1, measurements_cam2, measurements_cam3;
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// Project three landmarks into three cameras
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projectToMultipleCameras(cam1, cam2, cam3, landmark1, measurements_cam1);
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projectToMultipleCameras(cam1, cam2, cam3, landmark2, measurements_cam2);
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projectToMultipleCameras(cam1, cam2, cam3, landmark3, measurements_cam3);
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KeyVector views;
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views.push_back(x1);
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views.push_back(x2);
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views.push_back(x3);
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SmartFactor::shared_ptr smartFactor1(new SmartFactor(model, sharedK2));
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smartFactor1->add(measurements_cam1, views);
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SmartFactor::shared_ptr smartFactor2(new SmartFactor(model, sharedK2));
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smartFactor2->add(measurements_cam2, views);
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SmartFactor::shared_ptr smartFactor3(new SmartFactor(model, sharedK2));
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smartFactor3->add(measurements_cam3, views);
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const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
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NonlinearFactorGraph graph;
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graph.push_back(smartFactor1);
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graph.push_back(smartFactor2);
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graph.push_back(smartFactor3);
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graph.addPrior(x1, cam1.pose(), noisePrior);
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graph.addPrior(x2, cam2.pose(), noisePrior);
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Values groundTruth;
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groundTruth.insert(x1, cam1.pose());
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groundTruth.insert(x2, cam2.pose());
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groundTruth.insert(x3, cam3.pose());
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DOUBLES_EQUAL(0, graph.error(groundTruth), 1e-9);
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// Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI/10, 0., -M_PI/10), Point3(0.5,0.1,0.3)); // noise from regular projection factor test below
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Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI / 100, 0., -M_PI / 100),
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Point3(0.1, 0.1, 0.1)); // smaller noise
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Values values;
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values.insert(x1, cam1.pose());
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values.insert(x2, cam2.pose());
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// initialize third pose with some noise, we expect it to move back to original pose_above
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values.insert(x3, pose_above * noise_pose);
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EXPECT(
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assert_equal(
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Pose3(
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Rot3(0, -0.0314107591, 0.99950656, -0.99950656, -0.0313952598,
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-0.000986635786, 0.0314107591, -0.999013364, -0.0313952598),
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Point3(0.1, -0.1, 1.9)), values.at<Pose3>(x3)));
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Values result;
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LevenbergMarquardtOptimizer optimizer(graph, values, lmParams);
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result = optimizer.optimize();
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EXPECT(assert_equal(pose_above, result.at<Pose3>(x3), 1e-6));
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}
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/* *************************************************************************
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TEST( SmartProjectionPoseFactorRollingShutter, Factors ) {
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using namespace vanillaPose;
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// Default cameras for simple derivatives
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Rot3 R;
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static Cal3_S2::shared_ptr sharedK(new Cal3_S2(100, 100, 0, 0, 0));
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Camera cam1(Pose3(R, Point3(0, 0, 0)), sharedK), cam2(
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Pose3(R, Point3(1, 0, 0)), sharedK);
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// one landmarks 1m in front of camera
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Point3 landmark1(0, 0, 10);
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Point2Vector measurements_cam1;
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// Project 2 landmarks into 2 cameras
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measurements_cam1.push_back(cam1.project(landmark1));
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measurements_cam1.push_back(cam2.project(landmark1));
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// Create smart factors
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KeyVector views {x1, x2};
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SmartFactor::shared_ptr smartFactor1 = boost::make_shared<SmartFactor>(model, sharedK);
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smartFactor1->add(measurements_cam1, views);
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SmartFactor::Cameras cameras;
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cameras.push_back(cam1);
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cameras.push_back(cam2);
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// Make sure triangulation works
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CHECK(smartFactor1->triangulateSafe(cameras));
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CHECK(!smartFactor1->isDegenerate());
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CHECK(!smartFactor1->isPointBehindCamera());
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boost::optional<Point3> p = smartFactor1->point();
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CHECK(p);
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EXPECT(assert_equal(landmark1, *p));
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VectorValues zeroDelta;
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Vector6 delta;
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delta.setZero();
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zeroDelta.insert(x1, delta);
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zeroDelta.insert(x2, delta);
|
|
|
|
VectorValues perturbedDelta;
|
|
delta.setOnes();
|
|
perturbedDelta.insert(x1, delta);
|
|
perturbedDelta.insert(x2, delta);
|
|
double expectedError = 2500;
|
|
|
|
// After eliminating the point, A1 and A2 contain 2-rank information on cameras:
|
|
Matrix16 A1, A2;
|
|
A1 << -10, 0, 0, 0, 1, 0;
|
|
A2 << 10, 0, 1, 0, -1, 0;
|
|
A1 *= 10. / sigma;
|
|
A2 *= 10. / sigma;
|
|
Matrix expectedInformation; // filled below
|
|
{
|
|
// createHessianFactor
|
|
Matrix66 G11 = 0.5 * A1.transpose() * A1;
|
|
Matrix66 G12 = 0.5 * A1.transpose() * A2;
|
|
Matrix66 G22 = 0.5 * A2.transpose() * A2;
|
|
|
|
Vector6 g1;
|
|
g1.setZero();
|
|
Vector6 g2;
|
|
g2.setZero();
|
|
|
|
double f = 0;
|
|
|
|
RegularHessianFactor<6> expected(x1, x2, G11, G12, g1, G22, g2, f);
|
|
expectedInformation = expected.information();
|
|
|
|
boost::shared_ptr<RegularHessianFactor<6> > actual =
|
|
smartFactor1->createHessianFactor(cameras, 0.0);
|
|
EXPECT(assert_equal(expectedInformation, actual->information(), 1e-6));
|
|
EXPECT(assert_equal(expected, *actual, 1e-6));
|
|
EXPECT_DOUBLES_EQUAL(0, actual->error(zeroDelta), 1e-6);
|
|
EXPECT_DOUBLES_EQUAL(expectedError, actual->error(perturbedDelta), 1e-6);
|
|
}
|
|
|
|
{
|
|
Matrix26 F1;
|
|
F1.setZero();
|
|
F1(0, 1) = -100;
|
|
F1(0, 3) = -10;
|
|
F1(1, 0) = 100;
|
|
F1(1, 4) = -10;
|
|
Matrix26 F2;
|
|
F2.setZero();
|
|
F2(0, 1) = -101;
|
|
F2(0, 3) = -10;
|
|
F2(0, 5) = -1;
|
|
F2(1, 0) = 100;
|
|
F2(1, 2) = 10;
|
|
F2(1, 4) = -10;
|
|
Matrix E(4, 3);
|
|
E.setZero();
|
|
E(0, 0) = 10;
|
|
E(1, 1) = 10;
|
|
E(2, 0) = 10;
|
|
E(2, 2) = 1;
|
|
E(3, 1) = 10;
|
|
SmartFactor::FBlocks Fs = list_of<Matrix>(F1)(F2);
|
|
Vector b(4);
|
|
b.setZero();
|
|
|
|
// Create smart factors
|
|
KeyVector keys;
|
|
keys.push_back(x1);
|
|
keys.push_back(x2);
|
|
|
|
// createJacobianQFactor
|
|
SharedIsotropic n = noiseModel::Isotropic::Sigma(4, sigma);
|
|
Matrix3 P = (E.transpose() * E).inverse();
|
|
JacobianFactorQ<6, 2> expectedQ(keys, Fs, E, P, b, n);
|
|
EXPECT(assert_equal(expectedInformation, expectedQ.information(), 1e-6));
|
|
|
|
boost::shared_ptr<JacobianFactorQ<6, 2> > actualQ =
|
|
smartFactor1->createJacobianQFactor(cameras, 0.0);
|
|
CHECK(actualQ);
|
|
EXPECT(assert_equal(expectedInformation, actualQ->information(), 1e-6));
|
|
EXPECT(assert_equal(expectedQ, *actualQ));
|
|
EXPECT_DOUBLES_EQUAL(0, actualQ->error(zeroDelta), 1e-6);
|
|
EXPECT_DOUBLES_EQUAL(expectedError, actualQ->error(perturbedDelta), 1e-6);
|
|
|
|
// Whiten for RegularImplicitSchurFactor (does not have noise model)
|
|
model->WhitenSystem(E, b);
|
|
Matrix3 whiteP = (E.transpose() * E).inverse();
|
|
Fs[0] = model->Whiten(Fs[0]);
|
|
Fs[1] = model->Whiten(Fs[1]);
|
|
|
|
// createRegularImplicitSchurFactor
|
|
RegularImplicitSchurFactor<Camera> expected(keys, Fs, E, whiteP, b);
|
|
|
|
boost::shared_ptr<RegularImplicitSchurFactor<Camera> > actual =
|
|
smartFactor1->createRegularImplicitSchurFactor(cameras, 0.0);
|
|
CHECK(actual);
|
|
EXPECT(assert_equal(expectedInformation, expected.information(), 1e-6));
|
|
EXPECT(assert_equal(expectedInformation, actual->information(), 1e-6));
|
|
EXPECT(assert_equal(expected, *actual));
|
|
EXPECT_DOUBLES_EQUAL(0, actual->error(zeroDelta), 1e-6);
|
|
EXPECT_DOUBLES_EQUAL(expectedError, actual->error(perturbedDelta), 1e-6);
|
|
}
|
|
|
|
{
|
|
// createJacobianSVDFactor
|
|
Vector1 b;
|
|
b.setZero();
|
|
double s = sigma * sin(M_PI_4);
|
|
SharedIsotropic n = noiseModel::Isotropic::Sigma(4 - 3, sigma);
|
|
JacobianFactor expected(x1, s * A1, x2, s * A2, b, n);
|
|
EXPECT(assert_equal(expectedInformation, expected.information(), 1e-6));
|
|
|
|
boost::shared_ptr<JacobianFactor> actual =
|
|
smartFactor1->createJacobianSVDFactor(cameras, 0.0);
|
|
CHECK(actual);
|
|
EXPECT(assert_equal(expectedInformation, actual->information(), 1e-6));
|
|
EXPECT(assert_equal(expected, *actual));
|
|
EXPECT_DOUBLES_EQUAL(0, actual->error(zeroDelta), 1e-6);
|
|
EXPECT_DOUBLES_EQUAL(expectedError, actual->error(perturbedDelta), 1e-6);
|
|
}
|
|
}
|
|
|
|
/* *************************************************************************
|
|
TEST( SmartProjectionPoseFactorRollingShutter, 3poses_iterative_smart_projection_factor ) {
|
|
|
|
using namespace vanillaPose;
|
|
|
|
KeyVector views {x1, x2, x3};
|
|
|
|
Point2Vector measurements_cam1, measurements_cam2, measurements_cam3;
|
|
|
|
// Project three landmarks into three cameras
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark1, measurements_cam1);
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark2, measurements_cam2);
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark3, measurements_cam3);
|
|
|
|
SmartFactor::shared_ptr smartFactor1(new SmartFactor(model, sharedK));
|
|
smartFactor1->add(measurements_cam1, views);
|
|
|
|
SmartFactor::shared_ptr smartFactor2(new SmartFactor(model, sharedK));
|
|
smartFactor2->add(measurements_cam2, views);
|
|
|
|
SmartFactor::shared_ptr smartFactor3(new SmartFactor(model, sharedK));
|
|
smartFactor3->add(measurements_cam3, views);
|
|
|
|
const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
|
|
|
|
NonlinearFactorGraph graph;
|
|
graph.push_back(smartFactor1);
|
|
graph.push_back(smartFactor2);
|
|
graph.push_back(smartFactor3);
|
|
graph.addPrior(x1, cam1.pose(), noisePrior);
|
|
graph.addPrior(x2, cam2.pose(), noisePrior);
|
|
|
|
// Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI/10, 0., -M_PI/10), Point3(0.5,0.1,0.3)); // noise from regular projection factor test below
|
|
Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI / 100, 0., -M_PI / 100),
|
|
Point3(0.1, 0.1, 0.1)); // smaller noise
|
|
Values values;
|
|
values.insert(x1, cam1.pose());
|
|
values.insert(x2, cam2.pose());
|
|
// initialize third pose with some noise, we expect it to move back to original pose_above
|
|
values.insert(x3, pose_above * noise_pose);
|
|
EXPECT(
|
|
assert_equal(
|
|
Pose3(
|
|
Rot3(1.11022302e-16, -0.0314107591, 0.99950656, -0.99950656,
|
|
-0.0313952598, -0.000986635786, 0.0314107591, -0.999013364,
|
|
-0.0313952598), Point3(0.1, -0.1, 1.9)),
|
|
values.at<Pose3>(x3)));
|
|
|
|
Values result;
|
|
LevenbergMarquardtOptimizer optimizer(graph, values, lmParams);
|
|
result = optimizer.optimize();
|
|
EXPECT(assert_equal(pose_above, result.at<Pose3>(x3), 1e-7));
|
|
}
|
|
|
|
/* *************************************************************************
|
|
TEST( SmartProjectionPoseFactorRollingShutter, landmarkDistance ) {
|
|
|
|
using namespace vanillaPose;
|
|
|
|
double excludeLandmarksFutherThanDist = 2;
|
|
|
|
KeyVector views {x1, x2, x3};
|
|
|
|
Point2Vector measurements_cam1, measurements_cam2, measurements_cam3;
|
|
|
|
// Project three landmarks into three cameras
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark1, measurements_cam1);
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark2, measurements_cam2);
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark3, measurements_cam3);
|
|
|
|
SmartProjectionParams params;
|
|
params.setRankTolerance(1.0);
|
|
params.setLinearizationMode(gtsam::JACOBIAN_SVD);
|
|
params.setDegeneracyMode(gtsam::IGNORE_DEGENERACY);
|
|
params.setLandmarkDistanceThreshold(excludeLandmarksFutherThanDist);
|
|
params.setEnableEPI(false);
|
|
|
|
SmartFactor::shared_ptr smartFactor1(
|
|
new SmartFactor(model, sharedK, params));
|
|
smartFactor1->add(measurements_cam1, views);
|
|
|
|
SmartFactor::shared_ptr smartFactor2(
|
|
new SmartFactor(model, sharedK, params));
|
|
smartFactor2->add(measurements_cam2, views);
|
|
|
|
SmartFactor::shared_ptr smartFactor3(
|
|
new SmartFactor(model, sharedK, params));
|
|
smartFactor3->add(measurements_cam3, views);
|
|
|
|
const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
|
|
|
|
NonlinearFactorGraph graph;
|
|
graph.push_back(smartFactor1);
|
|
graph.push_back(smartFactor2);
|
|
graph.push_back(smartFactor3);
|
|
graph.addPrior(x1, cam1.pose(), noisePrior);
|
|
graph.addPrior(x2, cam2.pose(), noisePrior);
|
|
|
|
// Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI/10, 0., -M_PI/10), Point3(0.5,0.1,0.3)); // noise from regular projection factor test below
|
|
Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI / 100, 0., -M_PI / 100),
|
|
Point3(0.1, 0.1, 0.1)); // smaller noise
|
|
Values values;
|
|
values.insert(x1, cam1.pose());
|
|
values.insert(x2, cam2.pose());
|
|
values.insert(x3, pose_above * noise_pose);
|
|
|
|
// All factors are disabled and pose should remain where it is
|
|
Values result;
|
|
LevenbergMarquardtOptimizer optimizer(graph, values, lmParams);
|
|
result = optimizer.optimize();
|
|
EXPECT(assert_equal(values.at<Pose3>(x3), result.at<Pose3>(x3)));
|
|
}
|
|
|
|
/* *************************************************************************
|
|
TEST( SmartProjectionPoseFactorRollingShutter, dynamicOutlierRejection ) {
|
|
|
|
using namespace vanillaPose;
|
|
|
|
double excludeLandmarksFutherThanDist = 1e10;
|
|
double dynamicOutlierRejectionThreshold = 1; // max 1 pixel of average reprojection error
|
|
|
|
KeyVector views {x1, x2, x3};
|
|
|
|
// add fourth landmark
|
|
Point3 landmark4(5, -0.5, 1);
|
|
|
|
Point2Vector measurements_cam1, measurements_cam2, measurements_cam3,
|
|
measurements_cam4;
|
|
|
|
// Project 4 landmarks into three cameras
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark1, measurements_cam1);
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark2, measurements_cam2);
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark3, measurements_cam3);
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark4, measurements_cam4);
|
|
measurements_cam4.at(0) = measurements_cam4.at(0) + Point2(10, 10); // add outlier
|
|
|
|
SmartProjectionParams params;
|
|
params.setLinearizationMode(gtsam::JACOBIAN_SVD);
|
|
params.setLandmarkDistanceThreshold(excludeLandmarksFutherThanDist);
|
|
params.setDynamicOutlierRejectionThreshold(dynamicOutlierRejectionThreshold);
|
|
|
|
SmartFactor::shared_ptr smartFactor1(
|
|
new SmartFactor(model, sharedK, params));
|
|
smartFactor1->add(measurements_cam1, views);
|
|
|
|
SmartFactor::shared_ptr smartFactor2(
|
|
new SmartFactor(model, sharedK, params));
|
|
smartFactor2->add(measurements_cam2, views);
|
|
|
|
SmartFactor::shared_ptr smartFactor3(
|
|
new SmartFactor(model, sharedK, params));
|
|
smartFactor3->add(measurements_cam3, views);
|
|
|
|
SmartFactor::shared_ptr smartFactor4(
|
|
new SmartFactor(model, sharedK, params));
|
|
smartFactor4->add(measurements_cam4, views);
|
|
|
|
const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
|
|
|
|
NonlinearFactorGraph graph;
|
|
graph.push_back(smartFactor1);
|
|
graph.push_back(smartFactor2);
|
|
graph.push_back(smartFactor3);
|
|
graph.push_back(smartFactor4);
|
|
graph.addPrior(x1, cam1.pose(), noisePrior);
|
|
graph.addPrior(x2, cam2.pose(), noisePrior);
|
|
|
|
Values values;
|
|
values.insert(x1, cam1.pose());
|
|
values.insert(x2, cam2.pose());
|
|
values.insert(x3, cam3.pose());
|
|
|
|
// All factors are disabled and pose should remain where it is
|
|
Values result;
|
|
LevenbergMarquardtOptimizer optimizer(graph, values, lmParams);
|
|
result = optimizer.optimize();
|
|
EXPECT(assert_equal(cam3.pose(), result.at<Pose3>(x3)));
|
|
}
|
|
|
|
/* *************************************************************************
|
|
TEST( SmartProjectionPoseFactorRollingShutter, 3poses_projection_factor ) {
|
|
|
|
using namespace vanillaPose2;
|
|
|
|
KeyVector views {x1, x2, x3};
|
|
|
|
typedef GenericProjectionFactor<Pose3, Point3> ProjectionFactor;
|
|
NonlinearFactorGraph graph;
|
|
|
|
// Project three landmarks into three cameras
|
|
graph.emplace_shared<ProjectionFactor>(cam1.project(landmark1), model, x1, L(1), sharedK2);
|
|
graph.emplace_shared<ProjectionFactor>(cam2.project(landmark1), model, x2, L(1), sharedK2);
|
|
graph.emplace_shared<ProjectionFactor>(cam3.project(landmark1), model, x3, L(1), sharedK2);
|
|
|
|
graph.emplace_shared<ProjectionFactor>(cam1.project(landmark2), model, x1, L(2), sharedK2);
|
|
graph.emplace_shared<ProjectionFactor>(cam2.project(landmark2), model, x2, L(2), sharedK2);
|
|
graph.emplace_shared<ProjectionFactor>(cam3.project(landmark2), model, x3, L(2), sharedK2);
|
|
|
|
graph.emplace_shared<ProjectionFactor>(cam1.project(landmark3), model, x1, L(3), sharedK2);
|
|
graph.emplace_shared<ProjectionFactor>(cam2.project(landmark3), model, x2, L(3), sharedK2);
|
|
graph.emplace_shared<ProjectionFactor>(cam3.project(landmark3), model, x3, L(3), sharedK2);
|
|
|
|
const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
|
|
graph.addPrior(x1, level_pose, noisePrior);
|
|
graph.addPrior(x2, pose_right, noisePrior);
|
|
|
|
Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI / 10, 0., -M_PI / 10),
|
|
Point3(0.5, 0.1, 0.3));
|
|
Values values;
|
|
values.insert(x1, level_pose);
|
|
values.insert(x2, pose_right);
|
|
values.insert(x3, pose_above * noise_pose);
|
|
values.insert(L(1), landmark1);
|
|
values.insert(L(2), landmark2);
|
|
values.insert(L(3), landmark3);
|
|
|
|
DOUBLES_EQUAL(48406055, graph.error(values), 1);
|
|
|
|
LevenbergMarquardtOptimizer optimizer(graph, values, lmParams);
|
|
Values result = optimizer.optimize();
|
|
|
|
DOUBLES_EQUAL(0, graph.error(result), 1e-9);
|
|
|
|
EXPECT(assert_equal(pose_above, result.at<Pose3>(x3), 1e-7));
|
|
}
|
|
|
|
/* *************************************************************************
|
|
TEST( SmartProjectionPoseFactorRollingShutter, CheckHessian) {
|
|
|
|
KeyVector views {x1, x2, x3};
|
|
|
|
using namespace vanillaPose;
|
|
|
|
// Two slightly different cameras
|
|
Pose3 pose2 = level_pose
|
|
* Pose3(Rot3::RzRyRx(-0.05, 0.0, -0.05), Point3(0, 0, 0));
|
|
Pose3 pose3 = pose2 * Pose3(Rot3::RzRyRx(-0.05, 0.0, -0.05), Point3(0, 0, 0));
|
|
Camera cam2(pose2, sharedK);
|
|
Camera cam3(pose3, sharedK);
|
|
|
|
Point2Vector measurements_cam1, measurements_cam2, measurements_cam3;
|
|
|
|
// Project three landmarks into three cameras
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark1, measurements_cam1);
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark2, measurements_cam2);
|
|
projectToMultipleCameras(cam1, cam2, cam3, landmark3, measurements_cam3);
|
|
|
|
SmartProjectionParams params;
|
|
params.setRankTolerance(10);
|
|
|
|
SmartFactor::shared_ptr smartFactor1(
|
|
new SmartFactor(model, sharedK, params)); // HESSIAN, by default
|
|
smartFactor1->add(measurements_cam1, views);
|
|
|
|
SmartFactor::shared_ptr smartFactor2(
|
|
new SmartFactor(model, sharedK, params)); // HESSIAN, by default
|
|
smartFactor2->add(measurements_cam2, views);
|
|
|
|
SmartFactor::shared_ptr smartFactor3(
|
|
new SmartFactor(model, sharedK, params)); // HESSIAN, by default
|
|
smartFactor3->add(measurements_cam3, views);
|
|
|
|
NonlinearFactorGraph graph;
|
|
graph.push_back(smartFactor1);
|
|
graph.push_back(smartFactor2);
|
|
graph.push_back(smartFactor3);
|
|
|
|
// Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI/10, 0., -M_PI/10), Point3(0.5,0.1,0.3)); // noise from regular projection factor test below
|
|
Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI / 100, 0., -M_PI / 100),
|
|
Point3(0.1, 0.1, 0.1)); // smaller noise
|
|
Values values;
|
|
values.insert(x1, cam1.pose());
|
|
values.insert(x2, cam2.pose());
|
|
// initialize third pose with some noise, we expect it to move back to original pose_above
|
|
values.insert(x3, pose3 * noise_pose);
|
|
EXPECT(
|
|
assert_equal(
|
|
Pose3(
|
|
Rot3(0.00563056869, -0.130848107, 0.991386438, -0.991390265,
|
|
-0.130426831, -0.0115837907, 0.130819108, -0.98278564,
|
|
-0.130455917),
|
|
Point3(0.0897734171, -0.110201006, 0.901022872)),
|
|
values.at<Pose3>(x3)));
|
|
|
|
boost::shared_ptr<GaussianFactor> factor1 = smartFactor1->linearize(values);
|
|
boost::shared_ptr<GaussianFactor> factor2 = smartFactor2->linearize(values);
|
|
boost::shared_ptr<GaussianFactor> factor3 = smartFactor3->linearize(values);
|
|
|
|
Matrix CumulativeInformation = factor1->information() + factor2->information()
|
|
+ factor3->information();
|
|
|
|
boost::shared_ptr<GaussianFactorGraph> GaussianGraph = graph.linearize(
|
|
values);
|
|
Matrix GraphInformation = GaussianGraph->hessian().first;
|
|
|
|
// Check Hessian
|
|
EXPECT(assert_equal(GraphInformation, CumulativeInformation, 1e-6));
|
|
|
|
Matrix AugInformationMatrix = factor1->augmentedInformation()
|
|
+ factor2->augmentedInformation() + factor3->augmentedInformation();
|
|
|
|
// Check Information vector
|
|
Vector InfoVector = AugInformationMatrix.block(0, 18, 18, 1); // 18x18 Hessian + information vector
|
|
|
|
// Check Hessian
|
|
EXPECT(assert_equal(InfoVector, GaussianGraph->hessian().second, 1e-6));
|
|
}
|
|
|
|
/* *************************************************************************
|
|
TEST( SmartProjectionPoseFactorRollingShutter, Hessian ) {
|
|
|
|
using namespace vanillaPose2;
|
|
|
|
KeyVector views {x1, x2};
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// Project three landmarks into 2 cameras
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Point2 cam1_uv1 = cam1.project(landmark1);
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Point2 cam2_uv1 = cam2.project(landmark1);
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Point2Vector measurements_cam1;
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measurements_cam1.push_back(cam1_uv1);
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measurements_cam1.push_back(cam2_uv1);
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SmartFactor::shared_ptr smartFactor1(new SmartFactor(model, sharedK2));
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smartFactor1->add(measurements_cam1, views);
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Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI / 10, 0., -M_PI / 10),
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Point3(0.5, 0.1, 0.3));
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Values values;
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values.insert(x1, cam1.pose());
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values.insert(x2, cam2.pose());
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boost::shared_ptr<GaussianFactor> factor = smartFactor1->linearize(values);
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// compute triangulation from linearization point
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// compute reprojection errors (sum squared)
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// compare with factor.info(): the bottom right element is the squared sum of the reprojection errors (normalized by the covariance)
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// check that it is correctly scaled when using noiseProjection = [1/4 0; 0 1/4]
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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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