1385 lines
52 KiB
C++
1385 lines
52 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 testSmartProjectionFactorP.cpp
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* @brief Unit tests for SmartProjectionFactorP Class
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* @author Chris Beall
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* @author Luca Carlone
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* @author Zsolt Kira
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* @author Frank Dellaert
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* @date August 2021
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*/
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#include "smartFactorScenarios.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/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 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 Point2 measurement1(323.0, 240.0);
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LevenbergMarquardtParams lmParams;
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// Make more verbose like so (in tests):
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// params.verbosityLM = LevenbergMarquardtParams::SUMMARY;
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/* ************************************************************************* */
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TEST( SmartProjectionFactorP, Constructor) {
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using namespace vanillaPose;
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SmartFactorP::shared_ptr factor1(new SmartFactorP(model));
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactorP, Constructor2) {
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using namespace vanillaPose;
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SmartProjectionParams params;
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params.setRankTolerance(rankTol);
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SmartFactorP factor1(model, params);
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactorP, Constructor3) {
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using namespace vanillaPose;
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SmartFactorP::shared_ptr factor1(new SmartFactorP(model));
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factor1->add(measurement1, x1, sharedK);
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactorP, Constructor4) {
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using namespace vanillaPose;
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SmartProjectionParams params;
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params.setRankTolerance(rankTol);
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SmartFactorP factor1(model, params);
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factor1.add(measurement1, x1, sharedK);
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactorP, Equals ) {
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using namespace vanillaPose;
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SmartFactorP::shared_ptr factor1(new SmartFactorP(model));
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factor1->add(measurement1, x1, sharedK);
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SmartFactorP::shared_ptr factor2(new SmartFactorP(model));
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factor2->add(measurement1, x1, sharedK);
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CHECK(assert_equal(*factor1, *factor2));
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}
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/* *************************************************************************/
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TEST( SmartProjectionFactorP, noiseless ) {
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using namespace vanillaPose;
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// Project two landmarks into two cameras
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Point2 level_uv = level_camera.project(landmark1);
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Point2 level_uv_right = level_camera_right.project(landmark1);
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SmartFactorP factor(model);
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factor.add(level_uv, x1, sharedK);
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factor.add(level_uv_right, x2, sharedK);
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Values values; // it's a pose factor, hence these are poses
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values.insert(x1, cam1.pose());
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values.insert(x2, cam2.pose());
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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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SmartFactorP::Cameras cameras = factor.cameras(values);
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double actualError2 = factor.totalReprojectionError(cameras);
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EXPECT_DOUBLES_EQUAL(expectedError, actualError2, 1e-7);
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// Calculate expected derivative for point (easiest to check)
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std::function<Vector(Point3)> f = //
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std::bind(&SmartFactorP::whitenedError<Point3>, factor, cameras, std::placeholders::_1);
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// Calculate using computeEP
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Matrix actualE;
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factor.triangulateAndComputeE(actualE, values);
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// get point
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boost::optional<Point3> point = factor.point();
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CHECK(point);
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// calculate numerical derivative with triangulated point
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Matrix expectedE = sigma * numericalDerivative11<Vector, Point3>(f, *point);
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EXPECT(assert_equal(expectedE, actualE, 1e-7));
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// Calculate using reprojectionError
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SmartFactorP::Cameras::FBlocks F;
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Matrix E;
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Vector actualErrors = factor.unwhitenedError(cameras, *point, F, E);
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EXPECT(assert_equal(expectedE, E, 1e-7));
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EXPECT(assert_equal(Z_4x1, actualErrors, 1e-7));
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// Calculate using computeJacobians
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Vector b;
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SmartFactorP::FBlocks Fs;
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factor.computeJacobians(Fs, E, b, cameras, *point);
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double actualError3 = b.squaredNorm();
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EXPECT(assert_equal(expectedE, E, 1e-7));
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EXPECT_DOUBLES_EQUAL(expectedError, actualError3, 1e-6);
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}
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/* *************************************************************************/
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TEST( SmartProjectionFactorP, noisy ) {
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using namespace vanillaPose;
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// Project two landmarks into two cameras
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Point2 pixelError(0.2, 0.2);
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Point2 level_uv = level_camera.project(landmark1) + pixelError;
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Point2 level_uv_right = level_camera_right.project(landmark1);
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Values values;
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values.insert(x1, cam1.pose());
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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.insert(x2, pose_right.compose(noise_pose));
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SmartFactorP::shared_ptr factor(new SmartFactorP(model));
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factor->add(level_uv, x1, sharedK);
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factor->add(level_uv_right, x2, sharedK);
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double actualError1 = factor->error(values);
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SmartFactorP::shared_ptr factor2(new SmartFactorP(model));
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Point2Vector measurements;
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measurements.push_back(level_uv);
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measurements.push_back(level_uv_right);
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std::vector<boost::shared_ptr<Cal3_S2>> sharedKs;
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sharedKs.push_back(sharedK);
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sharedKs.push_back(sharedK);
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KeyVector views {x1, x2};
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factor2->add(measurements, views, sharedKs);
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double actualError2 = factor2->error(values);
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DOUBLES_EQUAL(actualError1, actualError2, 1e-7);
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}
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/* *************************************************************************/
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TEST(SmartProjectionFactorP, smartFactorWithSensorBodyTransform) {
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using namespace vanillaPose;
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// create arbitrary body_T_sensor (transforms from sensor to body)
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Pose3 body_T_sensor = Pose3(Rot3::Ypr(-M_PI / 2, 0., -M_PI / 2), Point3(1, 1, 1));
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// These are the poses we want to estimate, from camera measurements
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const Pose3 sensor_T_body = body_T_sensor.inverse();
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Pose3 wTb1 = cam1.pose() * sensor_T_body;
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Pose3 wTb2 = cam2.pose() * sensor_T_body;
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Pose3 wTb3 = cam3.pose() * sensor_T_body;
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// three landmarks ~5 meters infront of camera
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Point3 landmark1(5, 0.5, 1.2), landmark2(5, -0.5, 1.2), landmark3(5, 0, 3.0);
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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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// Create smart factors
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KeyVector views {x1, x2, x3};
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SmartProjectionParams params;
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params.setRankTolerance(1.0);
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params.setDegeneracyMode(IGNORE_DEGENERACY);
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params.setEnableEPI(false);
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std::vector<boost::shared_ptr<Cal3_S2>> sharedKs;
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sharedKs.push_back(sharedK);
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sharedKs.push_back(sharedK);
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sharedKs.push_back(sharedK);
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std::vector<Pose3> body_T_sensors;
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body_T_sensors.push_back(body_T_sensor);
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body_T_sensors.push_back(body_T_sensor);
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body_T_sensors.push_back(body_T_sensor);
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SmartFactorP smartFactor1(model, params);
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smartFactor1.add(measurements_cam1, views, sharedKs, body_T_sensors);
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SmartFactorP smartFactor2(model, params);
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smartFactor2.add(measurements_cam2, views, sharedKs, body_T_sensors);
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SmartFactorP smartFactor3(model, params);
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smartFactor3.add(measurements_cam3, views, sharedKs, body_T_sensors);;
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const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
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// Put all factors in factor graph, adding priors
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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, wTb1, noisePrior);
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graph.addPrior(x2, wTb2, noisePrior);
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// Check errors at ground truth poses
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Values gtValues;
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gtValues.insert(x1, wTb1);
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gtValues.insert(x2, wTb2);
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gtValues.insert(x3, wTb3);
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double actualError = graph.error(gtValues);
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double expectedError = 0.0;
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DOUBLES_EQUAL(expectedError, actualError, 1e-7)
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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));
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Values values;
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values.insert(x1, wTb1);
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values.insert(x2, wTb2);
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// initialize third pose with some noise, we expect it to move back to
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// original pose3
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values.insert(x3, wTb3 * noise_pose);
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LevenbergMarquardtParams lmParams;
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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(wTb3, result.at<Pose3>(x3)));
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}
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///* *************************************************************************/
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//TEST( SmartProjectionFactorP, 3poses_smart_projection_factor ) {
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//
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// using namespace vanillaPose2;
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// Point2Vector measurements_cam1, measurements_cam2, measurements_cam3;
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//
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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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//
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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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//
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// SmartFactorP::shared_ptr smartFactor1(new SmartFactorP(model, sharedK2));
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// smartFactor1->add(measurements_cam1, views);
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//
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// SmartFactorP::shared_ptr smartFactor2(new SmartFactorP(model, sharedK2));
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// smartFactor2->add(measurements_cam2, views);
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//
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// SmartFactorP::shared_ptr smartFactor3(new SmartFactorP(model, sharedK2));
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// smartFactor3->add(measurements_cam3, views);
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//
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// const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
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//
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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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//
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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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//
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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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//
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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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///* *************************************************************************/
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//TEST( SmartProjectionFactorP, Factors ) {
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//
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// using namespace vanillaPose;
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//
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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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//
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// // one landmarks 1m in front of camera
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// Point3 landmark1(0, 0, 10);
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//
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// Point2Vector measurements_cam1;
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//
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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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//
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// // Create smart factors
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// KeyVector views {x1, x2};
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//
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// SmartFactorP::shared_ptr smartFactor1 = boost::make_shared<SmartFactorP>(model, sharedK);
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// smartFactor1->add(measurements_cam1, views);
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//
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// SmartFactorP::Cameras cameras;
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// cameras.push_back(cam1);
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// cameras.push_back(cam2);
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//
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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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//
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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);
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//
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// VectorValues perturbedDelta;
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// delta.setOnes();
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// perturbedDelta.insert(x1, delta);
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// perturbedDelta.insert(x2, delta);
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// double expectedError = 2500;
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//
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// // After eliminating the point, A1 and A2 contain 2-rank information on cameras:
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// Matrix16 A1, A2;
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// A1 << -10, 0, 0, 0, 1, 0;
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// A2 << 10, 0, 1, 0, -1, 0;
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// A1 *= 10. / sigma;
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// A2 *= 10. / sigma;
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// Matrix expectedInformation; // filled below
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// {
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// // createHessianFactor
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// Matrix66 G11 = 0.5 * A1.transpose() * A1;
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// Matrix66 G12 = 0.5 * A1.transpose() * A2;
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// Matrix66 G22 = 0.5 * A2.transpose() * A2;
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//
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// Vector6 g1;
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// g1.setZero();
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// Vector6 g2;
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// g2.setZero();
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//
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// double f = 0;
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//
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// RegularHessianFactor<6> expected(x1, x2, G11, G12, g1, G22, g2, f);
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// expectedInformation = expected.information();
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//
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// boost::shared_ptr<RegularHessianFactor<6> > actual =
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// smartFactor1->createHessianFactor(cameras, 0.0);
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// EXPECT(assert_equal(expectedInformation, actual->information(), 1e-6));
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// EXPECT(assert_equal(expected, *actual, 1e-6));
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// EXPECT_DOUBLES_EQUAL(0, actual->error(zeroDelta), 1e-6);
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// EXPECT_DOUBLES_EQUAL(expectedError, actual->error(perturbedDelta), 1e-6);
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// }
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//
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// {
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// Matrix26 F1;
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// F1.setZero();
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// F1(0, 1) = -100;
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// F1(0, 3) = -10;
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// F1(1, 0) = 100;
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// F1(1, 4) = -10;
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// Matrix26 F2;
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// F2.setZero();
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// F2(0, 1) = -101;
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// F2(0, 3) = -10;
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// F2(0, 5) = -1;
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// F2(1, 0) = 100;
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// F2(1, 2) = 10;
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// F2(1, 4) = -10;
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// Matrix E(4, 3);
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// E.setZero();
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// E(0, 0) = 10;
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// E(1, 1) = 10;
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// E(2, 0) = 10;
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// E(2, 2) = 1;
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// E(3, 1) = 10;
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// SmartFactorP::FBlocks Fs = list_of<Matrix>(F1)(F2);
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// Vector b(4);
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// b.setZero();
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//
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// // Create smart factors
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// KeyVector keys;
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// keys.push_back(x1);
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// keys.push_back(x2);
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//
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// // createJacobianQFactor
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// SharedIsotropic n = noiseModel::Isotropic::Sigma(4, sigma);
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// Matrix3 P = (E.transpose() * E).inverse();
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// JacobianFactorQ<6, 2> expectedQ(keys, Fs, E, P, b, n);
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// EXPECT(assert_equal(expectedInformation, expectedQ.information(), 1e-6));
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//
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// boost::shared_ptr<JacobianFactorQ<6, 2> > actualQ =
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// smartFactor1->createJacobianQFactor(cameras, 0.0);
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// 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( SmartProjectionFactorP, 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);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor1(new SmartFactorP(model, sharedK));
|
|
// smartFactor1->add(measurements_cam1, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor2(new SmartFactorP(model, sharedK));
|
|
// smartFactor2->add(measurements_cam2, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor3(new SmartFactorP(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( SmartProjectionFactorP, jacobianSVD ) {
|
|
//
|
|
// 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);
|
|
//
|
|
// SmartProjectionParams params;
|
|
// params.setRankTolerance(1.0);
|
|
// params.setLinearizationMode(gtsam::JACOBIAN_SVD);
|
|
// params.setDegeneracyMode(gtsam::IGNORE_DEGENERACY);
|
|
// params.setEnableEPI(false);
|
|
// SmartFactorP factor1(model, sharedK, params);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor1(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor1->add(measurements_cam1, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor2(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor2->add(measurements_cam2, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor3(
|
|
// new SmartFactorP(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);
|
|
//
|
|
// Values result;
|
|
// LevenbergMarquardtOptimizer optimizer(graph, values, lmParams);
|
|
// result = optimizer.optimize();
|
|
// EXPECT(assert_equal(pose_above, result.at<Pose3>(x3), 1e-6));
|
|
//}
|
|
//
|
|
///* *************************************************************************/
|
|
//TEST( SmartProjectionFactorP, 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);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor1(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor1->add(measurements_cam1, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor2(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor2->add(measurements_cam2, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor3(
|
|
// new SmartFactorP(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( SmartProjectionFactorP, 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);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor1(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor1->add(measurements_cam1, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor2(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor2->add(measurements_cam2, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor3(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor3->add(measurements_cam3, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor4(
|
|
// new SmartFactorP(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( SmartProjectionFactorP, jacobianQ ) {
|
|
//
|
|
// 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);
|
|
//
|
|
// SmartProjectionParams params;
|
|
// params.setLinearizationMode(gtsam::JACOBIAN_Q);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor1(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor1->add(measurements_cam1, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor2(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor2->add(measurements_cam2, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor3(
|
|
// new SmartFactorP(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 / 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);
|
|
//
|
|
// Values result;
|
|
// LevenbergMarquardtOptimizer optimizer(graph, values, lmParams);
|
|
// result = optimizer.optimize();
|
|
// EXPECT(assert_equal(pose_above, result.at<Pose3>(x3), 1e-6));
|
|
//}
|
|
//
|
|
///* *************************************************************************/
|
|
//TEST( SmartProjectionFactorP, 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( SmartProjectionFactorP, 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);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor1(
|
|
// new SmartFactorP(model, sharedK, params)); // HESSIAN, by default
|
|
// smartFactor1->add(measurements_cam1, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor2(
|
|
// new SmartFactorP(model, sharedK, params)); // HESSIAN, by default
|
|
// smartFactor2->add(measurements_cam2, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor3(
|
|
// new SmartFactorP(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( SmartProjectionFactorP, 3poses_2land_rotation_only_smart_projection_factor ) {
|
|
// using namespace vanillaPose2;
|
|
//
|
|
// KeyVector views {x1, x2, x3};
|
|
//
|
|
// // Two different cameras, at the same position, but different rotations
|
|
// 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, sharedK2);
|
|
// Camera cam3(pose3, sharedK2);
|
|
//
|
|
// Point2Vector measurements_cam1, measurements_cam2;
|
|
//
|
|
// // Project three landmarks into three cameras
|
|
// projectToMultipleCameras(cam1, cam2, cam3, landmark1, measurements_cam1);
|
|
// projectToMultipleCameras(cam1, cam2, cam3, landmark2, measurements_cam2);
|
|
//
|
|
// SmartProjectionParams params;
|
|
// params.setRankTolerance(50);
|
|
// params.setDegeneracyMode(gtsam::HANDLE_INFINITY);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor1(
|
|
// new SmartFactorP(model, sharedK2, params));
|
|
// smartFactor1->add(measurements_cam1, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor2(
|
|
// new SmartFactorP(model, sharedK2, params));
|
|
// smartFactor2->add(measurements_cam2, views);
|
|
//
|
|
// const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
|
|
// const SharedDiagonal noisePriorTranslation = noiseModel::Isotropic::Sigma(3, 0.10);
|
|
// Point3 positionPrior = Point3(0, 0, 1);
|
|
//
|
|
// NonlinearFactorGraph graph;
|
|
// graph.push_back(smartFactor1);
|
|
// graph.push_back(smartFactor2);
|
|
// graph.addPrior(x1, cam1.pose(), noisePrior);
|
|
// graph.emplace_shared<PoseTranslationPrior<Pose3> >(x2, positionPrior, noisePriorTranslation);
|
|
// graph.emplace_shared<PoseTranslationPrior<Pose3> >(x3, positionPrior, noisePriorTranslation);
|
|
//
|
|
// 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, pose2 * noise_pose);
|
|
// values.insert(x3, pose3 * noise_pose);
|
|
//
|
|
// // params.verbosityLM = LevenbergMarquardtParams::SUMMARY;
|
|
// LevenbergMarquardtOptimizer optimizer(graph, values, lmParams);
|
|
// Values result = optimizer.optimize();
|
|
// EXPECT(assert_equal(pose3, result.at<Pose3>(x3)));
|
|
//}
|
|
//
|
|
///* *************************************************************************/
|
|
//TEST( SmartProjectionFactorP, 3poses_rotation_only_smart_projection_factor ) {
|
|
//
|
|
// // this test considers a condition in which the cheirality constraint is triggered
|
|
// using namespace vanillaPose;
|
|
//
|
|
// KeyVector views {x1, x2, x3};
|
|
//
|
|
// // Two different cameras, at the same position, but different rotations
|
|
// 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);
|
|
// params.setDegeneracyMode(gtsam::ZERO_ON_DEGENERACY);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor1(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor1->add(measurements_cam1, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor2(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor2->add(measurements_cam2, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor3(
|
|
// new SmartFactorP(model, sharedK, params));
|
|
// smartFactor3->add(measurements_cam3, views);
|
|
//
|
|
// const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
|
|
// const SharedDiagonal noisePriorTranslation = noiseModel::Isotropic::Sigma(3,
|
|
// 0.10);
|
|
// Point3 positionPrior = Point3(0, 0, 1);
|
|
//
|
|
// NonlinearFactorGraph graph;
|
|
// graph.push_back(smartFactor1);
|
|
// graph.push_back(smartFactor2);
|
|
// graph.push_back(smartFactor3);
|
|
// graph.addPrior(x1, cam1.pose(), noisePrior);
|
|
// graph.emplace_shared<PoseTranslationPrior<Pose3> >(x2, positionPrior, noisePriorTranslation);
|
|
// graph.emplace_shared<PoseTranslationPrior<Pose3> >(x3, positionPrior, noisePriorTranslation);
|
|
//
|
|
// // 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, 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)));
|
|
//
|
|
// Values result;
|
|
// LevenbergMarquardtOptimizer optimizer(graph, values, lmParams);
|
|
// result = optimizer.optimize();
|
|
//
|
|
// // Since we do not do anything on degenerate instances (ZERO_ON_DEGENERACY)
|
|
// // rotation remains the same as the initial guess, but position is fixed by PoseTranslationPrior
|
|
//#ifdef GTSAM_THROW_CHEIRALITY_EXCEPTION
|
|
// EXPECT(assert_equal(Pose3(values.at<Pose3>(x3).rotation(),
|
|
// Point3(0,0,1)), result.at<Pose3>(x3)));
|
|
//#else
|
|
// // if the check is disabled, no cheirality exception if thrown and the pose converges to the right rotation
|
|
// // with modest accuracy since the configuration is essentially degenerate without the translation due to noise (noise_pose)
|
|
// EXPECT(assert_equal(pose3, result.at<Pose3>(x3),1e-3));
|
|
//#endif
|
|
//}
|
|
//
|
|
///* *************************************************************************/
|
|
//TEST( SmartProjectionFactorP, Hessian ) {
|
|
//
|
|
// using namespace vanillaPose2;
|
|
//
|
|
// KeyVector views {x1, x2};
|
|
//
|
|
// // Project three landmarks into 2 cameras
|
|
// Point2 cam1_uv1 = cam1.project(landmark1);
|
|
// Point2 cam2_uv1 = cam2.project(landmark1);
|
|
// Point2Vector measurements_cam1;
|
|
// measurements_cam1.push_back(cam1_uv1);
|
|
// measurements_cam1.push_back(cam2_uv1);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor1(new SmartFactorP(model, sharedK2));
|
|
// smartFactor1->add(measurements_cam1, views);
|
|
//
|
|
// 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, cam1.pose());
|
|
// values.insert(x2, cam2.pose());
|
|
//
|
|
// boost::shared_ptr<GaussianFactor> factor = smartFactor1->linearize(values);
|
|
//
|
|
// // compute triangulation from linearization point
|
|
// // compute reprojection errors (sum squared)
|
|
// // compare with factor.info(): the bottom right element is the squared sum of the reprojection errors (normalized by the covariance)
|
|
// // check that it is correctly scaled when using noiseProjection = [1/4 0; 0 1/4]
|
|
//}
|
|
//
|
|
///* *************************************************************************/
|
|
//TEST( SmartProjectionFactorP, HessianWithRotation ) {
|
|
// // cout << " ************************ SmartProjectionFactorP: rotated Hessian **********************" << endl;
|
|
//
|
|
// using namespace vanillaPose;
|
|
//
|
|
// KeyVector views {x1, x2, x3};
|
|
//
|
|
// Point2Vector measurements_cam1, measurements_cam2, measurements_cam3;
|
|
//
|
|
// projectToMultipleCameras(cam1, cam2, cam3, landmark1, measurements_cam1);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactorInstance(new SmartFactorP(model, sharedK));
|
|
// smartFactorInstance->add(measurements_cam1, views);
|
|
//
|
|
// Values values;
|
|
// values.insert(x1, cam1.pose());
|
|
// values.insert(x2, cam2.pose());
|
|
// values.insert(x3, cam3.pose());
|
|
//
|
|
// boost::shared_ptr<GaussianFactor> factor = smartFactorInstance->linearize(
|
|
// values);
|
|
//
|
|
// Pose3 poseDrift = Pose3(Rot3::Ypr(-M_PI / 2, 0., -M_PI / 2), Point3(0, 0, 0));
|
|
//
|
|
// Values rotValues;
|
|
// rotValues.insert(x1, poseDrift.compose(level_pose));
|
|
// rotValues.insert(x2, poseDrift.compose(pose_right));
|
|
// rotValues.insert(x3, poseDrift.compose(pose_above));
|
|
//
|
|
// boost::shared_ptr<GaussianFactor> factorRot = smartFactorInstance->linearize(
|
|
// rotValues);
|
|
//
|
|
// // Hessian is invariant to rotations in the nondegenerate case
|
|
// EXPECT(assert_equal(factor->information(), factorRot->information(), 1e-7));
|
|
//
|
|
// Pose3 poseDrift2 = Pose3(Rot3::Ypr(-M_PI / 2, -M_PI / 3, -M_PI / 2),
|
|
// Point3(10, -4, 5));
|
|
//
|
|
// Values tranValues;
|
|
// tranValues.insert(x1, poseDrift2.compose(level_pose));
|
|
// tranValues.insert(x2, poseDrift2.compose(pose_right));
|
|
// tranValues.insert(x3, poseDrift2.compose(pose_above));
|
|
//
|
|
// boost::shared_ptr<GaussianFactor> factorRotTran =
|
|
// smartFactorInstance->linearize(tranValues);
|
|
//
|
|
// // Hessian is invariant to rotations and translations in the nondegenerate case
|
|
// EXPECT(assert_equal(factor->information(), factorRotTran->information(), 1e-7));
|
|
//}
|
|
//
|
|
///* *************************************************************************/
|
|
//TEST( SmartProjectionFactorP, HessianWithRotationDegenerate ) {
|
|
//
|
|
// using namespace vanillaPose2;
|
|
//
|
|
// KeyVector views {x1, x2, x3};
|
|
//
|
|
// // All cameras have the same pose so will be degenerate !
|
|
// Camera cam2(level_pose, sharedK2);
|
|
// Camera cam3(level_pose, sharedK2);
|
|
//
|
|
// Point2Vector measurements_cam1;
|
|
// projectToMultipleCameras(cam1, cam2, cam3, landmark1, measurements_cam1);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor(new SmartFactorP(model, sharedK2));
|
|
// smartFactor->add(measurements_cam1, views);
|
|
//
|
|
// Values values;
|
|
// values.insert(x1, cam1.pose());
|
|
// values.insert(x2, cam2.pose());
|
|
// values.insert(x3, cam3.pose());
|
|
//
|
|
// boost::shared_ptr<GaussianFactor> factor = smartFactor->linearize(values);
|
|
//
|
|
// Pose3 poseDrift = Pose3(Rot3::Ypr(-M_PI / 2, 0., -M_PI / 2), Point3(0, 0, 0));
|
|
//
|
|
// Values rotValues;
|
|
// rotValues.insert(x1, poseDrift.compose(level_pose));
|
|
// rotValues.insert(x2, poseDrift.compose(level_pose));
|
|
// rotValues.insert(x3, poseDrift.compose(level_pose));
|
|
//
|
|
// boost::shared_ptr<GaussianFactor> factorRot = //
|
|
// smartFactor->linearize(rotValues);
|
|
//
|
|
// // Hessian is invariant to rotations in the nondegenerate case
|
|
// EXPECT(assert_equal(factor->information(), factorRot->information(), 1e-7));
|
|
//
|
|
// Pose3 poseDrift2 = Pose3(Rot3::Ypr(-M_PI / 2, -M_PI / 3, -M_PI / 2),
|
|
// Point3(10, -4, 5));
|
|
//
|
|
// Values tranValues;
|
|
// tranValues.insert(x1, poseDrift2.compose(level_pose));
|
|
// tranValues.insert(x2, poseDrift2.compose(level_pose));
|
|
// tranValues.insert(x3, poseDrift2.compose(level_pose));
|
|
//
|
|
// boost::shared_ptr<GaussianFactor> factorRotTran = smartFactor->linearize(
|
|
// tranValues);
|
|
//
|
|
// // Hessian is invariant to rotations and translations in the nondegenerate case
|
|
// EXPECT(assert_equal(factor->information(), factorRotTran->information(), 1e-7));
|
|
//}
|
|
//
|
|
///* ************************************************************************* */
|
|
//TEST( SmartProjectionFactorP, ConstructorWithCal3Bundler) {
|
|
// using namespace bundlerPose;
|
|
// SmartProjectionParams params;
|
|
// params.setDegeneracyMode(gtsam::ZERO_ON_DEGENERACY);
|
|
// SmartFactorP factor(model, sharedBundlerK, params);
|
|
// factor.add(measurement1, x1);
|
|
//}
|
|
//
|
|
///* *************************************************************************/
|
|
//TEST( SmartProjectionFactorP, Cal3Bundler ) {
|
|
//
|
|
// using namespace bundlerPose;
|
|
//
|
|
// // three landmarks ~5 meters in front of camera
|
|
// Point3 landmark3(3, 0, 3.0);
|
|
//
|
|
// 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);
|
|
//
|
|
// KeyVector views {x1, x2, x3};
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor1(new SmartFactorP(model, sharedBundlerK));
|
|
// smartFactor1->add(measurements_cam1, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor2(new SmartFactorP(model, sharedBundlerK));
|
|
// smartFactor2->add(measurements_cam2, views);
|
|
//
|
|
// SmartFactorP::shared_ptr smartFactor3(new SmartFactorP(model, sharedBundlerK));
|
|
// 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(0, -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(cam3.pose(), result.at<Pose3>(x3), 1e-6));
|
|
//}
|
|
//
|
|
///* *************************************************************************/
|
|
//TEST( SmartProjectionFactorP, Cal3BundlerRotationOnly ) {
|
|
//
|
|
// using namespace bundlerPose;
|
|
//
|
|
// KeyVector views {x1, x2, x3};
|
|
//
|
|
// // Two different cameras
|
|
// Pose3 pose2 = level_pose
|
|
// * Pose3(Rot3::RzRyRx(-0.05, 0.0, -0.05), Point3(0, 0, 0));
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// Pose3 pose3 = pose2 * Pose3(Rot3::RzRyRx(-0.05, 0.0, -0.05), Point3(0, 0, 0));
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// Camera cam2(pose2, sharedBundlerK);
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// Camera cam3(pose3, sharedBundlerK);
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//
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// // landmark3 at 3 meters now
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// Point3 landmark3(3, 0, 3.0);
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//
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// Point2Vector measurements_cam1, measurements_cam2, measurements_cam3;
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//
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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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//
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// SmartProjectionParams params;
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// params.setRankTolerance(10);
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// params.setDegeneracyMode(gtsam::ZERO_ON_DEGENERACY);
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//
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// SmartFactorP::shared_ptr smartFactor1(
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// new SmartFactorP(model, sharedBundlerK, params));
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// smartFactor1->add(measurements_cam1, views);
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//
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// SmartFactorP::shared_ptr smartFactor2(
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// new SmartFactorP(model, sharedBundlerK, params));
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// smartFactor2->add(measurements_cam2, views);
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//
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// SmartFactorP::shared_ptr smartFactor3(
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// new SmartFactorP(model, sharedBundlerK, params));
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// smartFactor3->add(measurements_cam3, views);
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//
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// const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
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// const SharedDiagonal noisePriorTranslation = noiseModel::Isotropic::Sigma(3,
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// 0.10);
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// Point3 positionPrior = Point3(0, 0, 1);
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//
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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.emplace_shared<PoseTranslationPrior<Pose3> >(x2, positionPrior, noisePriorTranslation);
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// graph.emplace_shared<PoseTranslationPrior<Pose3> >(x3, positionPrior, noisePriorTranslation);
|
|
//
|
|
// // 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)));
|
|
//
|
|
// Values result;
|
|
// LevenbergMarquardtOptimizer optimizer(graph, values, lmParams);
|
|
// result = optimizer.optimize();
|
|
//
|
|
// 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_CLASS_EXPORT_GUID(gtsam::noiseModel::Constrained, "gtsam_noiseModel_Constrained");
|
|
//BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Diagonal, "gtsam_noiseModel_Diagonal");
|
|
//BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Gaussian, "gtsam_noiseModel_Gaussian");
|
|
//BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Unit, "gtsam_noiseModel_Unit");
|
|
//BOOST_CLASS_EXPORT_GUID(gtsam::noiseModel::Isotropic, "gtsam_noiseModel_Isotropic");
|
|
//BOOST_CLASS_EXPORT_GUID(gtsam::SharedNoiseModel, "gtsam_SharedNoiseModel");
|
|
//BOOST_CLASS_EXPORT_GUID(gtsam::SharedDiagonal, "gtsam_SharedDiagonal");
|
|
//
|
|
//TEST(SmartProjectionFactorP, serialize) {
|
|
// using namespace vanillaPose;
|
|
// using namespace gtsam::serializationTestHelpers;
|
|
// SmartProjectionParams params;
|
|
// params.setRankTolerance(rankTol);
|
|
// SmartFactorP factor(model, sharedK, params);
|
|
//
|
|
// EXPECT(equalsObj(factor));
|
|
// EXPECT(equalsXML(factor));
|
|
// EXPECT(equalsBinary(factor));
|
|
//}
|
|
//
|
|
//TEST(SmartProjectionFactorP, serialize2) {
|
|
// using namespace vanillaPose;
|
|
// using namespace gtsam::serializationTestHelpers;
|
|
// SmartProjectionParams params;
|
|
// params.setRankTolerance(rankTol);
|
|
// Pose3 bts;
|
|
// SmartFactorP factor(model, sharedK, bts, params);
|
|
//
|
|
// // insert some measurments
|
|
// KeyVector key_view;
|
|
// Point2Vector meas_view;
|
|
// key_view.push_back(Symbol('x', 1));
|
|
// meas_view.push_back(Point2(10, 10));
|
|
// factor.add(meas_view, key_view);
|
|
//
|
|
// EXPECT(equalsObj(factor));
|
|
// EXPECT(equalsXML(factor));
|
|
// EXPECT(equalsBinary(factor));
|
|
//}
|
|
|
|
/* ************************************************************************* */
|
|
int main() {
|
|
TestResult tr;
|
|
return TestRegistry::runAllTests(tr);
|
|
}
|
|
/* ************************************************************************* */
|
|
|