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lcarlone
parent
0194e3df94
commit
c1da490c2d
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@ -366,20 +366,20 @@ TEST( SmartStereoProjectionFactorPP, noisy ) {
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DOUBLES_EQUAL(actualError1, 5381978, 1); // value freeze
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}
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/* *************************************************************************
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/* *************************************************************************/
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TEST( SmartStereoProjectionFactorPP, 3poses_smart_projection_factor ) {
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// create first camera. Looking along X-axis, 1 meter above ground plane (x-y)
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Pose3 pose1 = Pose3(Rot3::Ypr(-M_PI / 2, 0., -M_PI / 2), Point3(0, 0, 1));
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StereoCamera cam1(pose1, K2);
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Pose3 w_Pose_cam1 = Pose3(Rot3::Ypr(-M_PI / 2, 0., -M_PI / 2), Point3(0, 0, 1));
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StereoCamera cam1(w_Pose_cam1, K2);
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// create second camera 1 meter to the right of first camera
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Pose3 pose2 = pose1 * Pose3(Rot3(), Point3(1, 0, 0));
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StereoCamera cam2(pose2, K2);
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Pose3 w_Pose_cam2 = w_Pose_cam1 * Pose3(Rot3(), Point3(1, 0, 0));
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StereoCamera cam2(w_Pose_cam2, K2);
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// create third camera 1 meter above the first camera
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Pose3 pose3 = pose1 * Pose3(Rot3(), Point3(0, -1, 0));
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StereoCamera cam3(pose3, K2);
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Pose3 w_Pose_cam3 = w_Pose_cam1 * Pose3(Rot3(), Point3(0, -1, 0));
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StereoCamera cam3(w_Pose_cam3, K2);
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// three landmarks ~5 meters infront of camera
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Point3 landmark1(5, 0.5, 1.2);
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@ -394,116 +394,136 @@ TEST( SmartStereoProjectionFactorPP, 3poses_smart_projection_factor ) {
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vector<StereoPoint2> measurements_l3 = stereo_projectToMultipleCameras(cam1,
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cam2, cam3, landmark3);
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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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KeyVector poseKeys;
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poseKeys.push_back(x1);
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poseKeys.push_back(x2);
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poseKeys.push_back(x3);
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KeyVector extrinsicKeys;
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extrinsicKeys.push_back(body_P_cam1_key);
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extrinsicKeys.push_back(body_P_cam2_key);
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extrinsicKeys.push_back(body_P_cam3_key);
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SmartStereoProjectionParams smart_params;
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smart_params.triangulation.enableEPI = true;
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SmartStereoProjectionFactorPP::shared_ptr smartFactor1(new SmartStereoProjectionFactorPP(model, smart_params));
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smartFactor1->add(measurements_l1, views, K2);
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smartFactor1->add(measurements_l1, poseKeys, extrinsicKeys, K2);
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SmartStereoProjectionFactorPP::shared_ptr smartFactor2(new SmartStereoProjectionFactorPP(model, smart_params));
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smartFactor2->add(measurements_l2, views, K2);
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smartFactor2->add(measurements_l2, poseKeys, extrinsicKeys, K2);
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SmartStereoProjectionFactorPP::shared_ptr smartFactor3(new SmartStereoProjectionFactorPP(model, smart_params));
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smartFactor3->add(measurements_l3, views, K2);
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smartFactor3->add(measurements_l3, poseKeys, extrinsicKeys, K2);
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const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
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// Values
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Pose3 body_Pose_cam1 = Pose3(Rot3::Ypr(-M_PI, 1., 0.1),Point3(0, 1, 0));
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Pose3 body_Pose_cam2 = Pose3(Rot3::Ypr(-M_PI / 4, 0.1, 1.0),Point3(1, 1, 1));
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Pose3 body_Pose_cam3 = Pose3::identity();
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Pose3 w_Pose_body1 = w_Pose_cam1.compose(body_Pose_cam1.inverse());
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Pose3 w_Pose_body2 = w_Pose_cam2.compose(body_Pose_cam2.inverse());
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Pose3 w_Pose_body3 = w_Pose_cam3.compose(body_Pose_cam3.inverse());
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Values values;
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Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI / 100, 0., -M_PI / 100), Point3(0.1, 0.1, 0.1)); // smaller noise
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values.insert(x1, w_Pose_body1);
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values.insert(x2, w_Pose_body2);
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values.insert(x3, w_Pose_body3);
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values.insert(body_P_cam1_key, body_Pose_cam1);
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values.insert(body_P_cam2_key, body_Pose_cam2);
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// initialize third calibration with some noise, we expect it to move back to original pose3
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values.insert(body_P_cam3_key, body_Pose_cam3 * noise_pose);
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// Graph
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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, pose1, noisePrior);
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graph.addPrior(x2, pose2, noisePrior);
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graph.addPrior(x1, w_Pose_body1, noisePrior);
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graph.addPrior(x2, w_Pose_body2, noisePrior);
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graph.addPrior(x3, w_Pose_body3, noisePrior);
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// we might need some prior on the calibration too
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graph.addPrior(body_P_cam1_key, body_Pose_cam1, noisePrior);
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graph.addPrior(body_P_cam2_key, body_Pose_cam2, noisePrior);
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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, pose1);
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values.insert(x2, pose2);
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// initialize third pose with some noise, we expect it to move back to original pose3
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values.insert(x3, pose3 * 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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Point3(0.1, -0.1, 1.9)), values.at<Pose3>(x3) * values.at<Pose3>(body_P_cam3_key)));
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// cout << std::setprecision(10) << "\n----SmartStereoFactor graph initial error: " << graph.error(values) << endl;
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EXPECT_DOUBLES_EQUAL(833953.92789459578, graph.error(values), 1e-7); // initial error
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// get triangulated landmarks from smart factors
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Point3 landmark1_smart = *smartFactor1->point();
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Point3 landmark2_smart = *smartFactor2->point();
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Point3 landmark3_smart = *smartFactor3->point();
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// // get triangulated landmarks from smart factors
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// Point3 landmark1_smart = *smartFactor1->point();
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// Point3 landmark2_smart = *smartFactor2->point();
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// Point3 landmark3_smart = *smartFactor3->point();
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//
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// Values result;
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// gttic_(SmartStereoProjectionFactorPP);
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// LevenbergMarquardtOptimizer optimizer(graph, values, lm_params);
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// result = optimizer.optimize();
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// gttoc_(SmartStereoProjectionFactorPP);
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// tictoc_finishedIteration_();
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//
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// EXPECT_DOUBLES_EQUAL(0, graph.error(result), 1e-5);
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Values result;
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gttic_(SmartStereoProjectionFactorPP);
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LevenbergMarquardtOptimizer optimizer(graph, values, lm_params);
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result = optimizer.optimize();
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gttoc_(SmartStereoProjectionFactorPP);
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tictoc_finishedIteration_();
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EXPECT_DOUBLES_EQUAL(0, graph.error(result), 1e-5);
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// cout << std::setprecision(10) << "SmartStereoFactor graph optimized error: " << graph.error(result) << endl;
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GaussianFactorGraph::shared_ptr GFG = graph.linearize(result);
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VectorValues delta = GFG->optimize();
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VectorValues expected = VectorValues::Zero(delta);
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EXPECT(assert_equal(expected, delta, 1e-6));
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// result.print("results of 3 camera, 3 landmark optimization \n");
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EXPECT(assert_equal(pose3, result.at<Pose3>(x3)));
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// ***************************************************************
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// Same problem with regular Stereo factors, expect same error!
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// ****************************************************************
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// landmark1_smart.print("landmark1_smart");
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// landmark2_smart.print("landmark2_smart");
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// landmark3_smart.print("landmark3_smart");
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// add landmarks to values
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values.insert(L(1), landmark1_smart);
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values.insert(L(2), landmark2_smart);
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values.insert(L(3), landmark3_smart);
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// add factors
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NonlinearFactorGraph graph2;
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graph2.addPrior(x1, pose1, noisePrior);
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graph2.addPrior(x2, pose2, noisePrior);
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typedef GenericStereoFactor<Pose3, Point3> ProjectionFactor;
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bool verboseCheirality = true;
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graph2.push_back(ProjectionFactor(measurements_l1[0], model, x1, L(1), K2, false, verboseCheirality));
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graph2.push_back(ProjectionFactor(measurements_l1[1], model, x2, L(1), K2, false, verboseCheirality));
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graph2.push_back(ProjectionFactor(measurements_l1[2], model, x3, L(1), K2, false, verboseCheirality));
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graph2.push_back(ProjectionFactor(measurements_l2[0], model, x1, L(2), K2, false, verboseCheirality));
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graph2.push_back(ProjectionFactor(measurements_l2[1], model, x2, L(2), K2, false, verboseCheirality));
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graph2.push_back(ProjectionFactor(measurements_l2[2], model, x3, L(2), K2, false, verboseCheirality));
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graph2.push_back(ProjectionFactor(measurements_l3[0], model, x1, L(3), K2, false, verboseCheirality));
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graph2.push_back(ProjectionFactor(measurements_l3[1], model, x2, L(3), K2, false, verboseCheirality));
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graph2.push_back(ProjectionFactor(measurements_l3[2], model, x3, L(3), K2, false, verboseCheirality));
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// cout << std::setprecision(10) << "\n----StereoFactor graph initial error: " << graph2.error(values) << endl;
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EXPECT_DOUBLES_EQUAL(833953.92789459578, graph2.error(values), 1e-7);
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LevenbergMarquardtOptimizer optimizer2(graph2, values, lm_params);
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Values result2 = optimizer2.optimize();
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EXPECT_DOUBLES_EQUAL(0, graph2.error(result2), 1e-5);
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// cout << std::setprecision(10) << "StereoFactor graph optimized error: " << graph2.error(result2) << endl;
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//// cout << std::setprecision(10) << "SmartStereoFactor graph optimized error: " << graph.error(result) << endl;
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//
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// GaussianFactorGraph::shared_ptr GFG = graph.linearize(result);
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// VectorValues delta = GFG->optimize();
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// VectorValues expected = VectorValues::Zero(delta);
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// EXPECT(assert_equal(expected, delta, 1e-6));
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//
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// // result.print("results of 3 camera, 3 landmark optimization \n");
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// EXPECT(assert_equal(w_Pose_cam3, result.at<Pose3>(x3)));
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//
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// // ***************************************************************
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// // Same problem with regular Stereo factors, expect same error!
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// // ****************************************************************
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//
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//// landmark1_smart.print("landmark1_smart");
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//// landmark2_smart.print("landmark2_smart");
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//// landmark3_smart.print("landmark3_smart");
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//
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// // add landmarks to values
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// values.insert(L(1), landmark1_smart);
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// values.insert(L(2), landmark2_smart);
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// values.insert(L(3), landmark3_smart);
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//
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// // add factors
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// NonlinearFactorGraph graph2;
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//
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// graph2.addPrior(x1, w_Pose_cam1, noisePrior);
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// graph2.addPrior(x2, w_Pose_cam2, noisePrior);
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//
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// typedef GenericStereoFactor<Pose3, Point3> ProjectionFactor;
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//
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// bool verboseCheirality = true;
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//
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// graph2.push_back(ProjectionFactor(measurements_l1[0], model, x1, L(1), K2, false, verboseCheirality));
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// graph2.push_back(ProjectionFactor(measurements_l1[1], model, x2, L(1), K2, false, verboseCheirality));
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// graph2.push_back(ProjectionFactor(measurements_l1[2], model, x3, L(1), K2, false, verboseCheirality));
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//
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// graph2.push_back(ProjectionFactor(measurements_l2[0], model, x1, L(2), K2, false, verboseCheirality));
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// graph2.push_back(ProjectionFactor(measurements_l2[1], model, x2, L(2), K2, false, verboseCheirality));
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// graph2.push_back(ProjectionFactor(measurements_l2[2], model, x3, L(2), K2, false, verboseCheirality));
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//
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// graph2.push_back(ProjectionFactor(measurements_l3[0], model, x1, L(3), K2, false, verboseCheirality));
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// graph2.push_back(ProjectionFactor(measurements_l3[1], model, x2, L(3), K2, false, verboseCheirality));
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// graph2.push_back(ProjectionFactor(measurements_l3[2], model, x3, L(3), K2, false, verboseCheirality));
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//
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//// cout << std::setprecision(10) << "\n----StereoFactor graph initial error: " << graph2.error(values) << endl;
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// EXPECT_DOUBLES_EQUAL(833953.92789459578, graph2.error(values), 1e-7);
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//
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// LevenbergMarquardtOptimizer optimizer2(graph2, values, lm_params);
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// Values result2 = optimizer2.optimize();
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// EXPECT_DOUBLES_EQUAL(0, graph2.error(result2), 1e-5);
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//
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//// cout << std::setprecision(10) << "StereoFactor graph optimized error: " << graph2.error(result2) << endl;
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}
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/* *************************************************************************
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