diff --git a/gtsam_unstable/slam/tests/testSmartStereoProjectionFactorPP.cpp b/gtsam_unstable/slam/tests/testSmartStereoProjectionFactorPP.cpp index 78bf600f7..6ac2264b9 100644 --- a/gtsam_unstable/slam/tests/testSmartStereoProjectionFactorPP.cpp +++ b/gtsam_unstable/slam/tests/testSmartStereoProjectionFactorPP.cpp @@ -366,20 +366,20 @@ TEST( SmartStereoProjectionFactorPP, noisy ) { DOUBLES_EQUAL(actualError1, 5381978, 1); // value freeze } -/* ************************************************************************* +/* *************************************************************************/ TEST( SmartStereoProjectionFactorPP, 3poses_smart_projection_factor ) { // create first camera. Looking along X-axis, 1 meter above ground plane (x-y) - Pose3 pose1 = Pose3(Rot3::Ypr(-M_PI / 2, 0., -M_PI / 2), Point3(0, 0, 1)); - StereoCamera cam1(pose1, K2); + Pose3 w_Pose_cam1 = Pose3(Rot3::Ypr(-M_PI / 2, 0., -M_PI / 2), Point3(0, 0, 1)); + StereoCamera cam1(w_Pose_cam1, K2); // create second camera 1 meter to the right of first camera - Pose3 pose2 = pose1 * Pose3(Rot3(), Point3(1, 0, 0)); - StereoCamera cam2(pose2, K2); + Pose3 w_Pose_cam2 = w_Pose_cam1 * Pose3(Rot3(), Point3(1, 0, 0)); + StereoCamera cam2(w_Pose_cam2, K2); // create third camera 1 meter above the first camera - Pose3 pose3 = pose1 * Pose3(Rot3(), Point3(0, -1, 0)); - StereoCamera cam3(pose3, K2); + Pose3 w_Pose_cam3 = w_Pose_cam1 * Pose3(Rot3(), Point3(0, -1, 0)); + StereoCamera cam3(w_Pose_cam3, K2); // three landmarks ~5 meters infront of camera Point3 landmark1(5, 0.5, 1.2); @@ -394,116 +394,136 @@ TEST( SmartStereoProjectionFactorPP, 3poses_smart_projection_factor ) { vector measurements_l3 = stereo_projectToMultipleCameras(cam1, cam2, cam3, landmark3); - KeyVector views; - views.push_back(x1); - views.push_back(x2); - views.push_back(x3); + KeyVector poseKeys; + poseKeys.push_back(x1); + poseKeys.push_back(x2); + poseKeys.push_back(x3); + + KeyVector extrinsicKeys; + extrinsicKeys.push_back(body_P_cam1_key); + extrinsicKeys.push_back(body_P_cam2_key); + extrinsicKeys.push_back(body_P_cam3_key); SmartStereoProjectionParams smart_params; smart_params.triangulation.enableEPI = true; SmartStereoProjectionFactorPP::shared_ptr smartFactor1(new SmartStereoProjectionFactorPP(model, smart_params)); - smartFactor1->add(measurements_l1, views, K2); + smartFactor1->add(measurements_l1, poseKeys, extrinsicKeys, K2); SmartStereoProjectionFactorPP::shared_ptr smartFactor2(new SmartStereoProjectionFactorPP(model, smart_params)); - smartFactor2->add(measurements_l2, views, K2); + smartFactor2->add(measurements_l2, poseKeys, extrinsicKeys, K2); SmartStereoProjectionFactorPP::shared_ptr smartFactor3(new SmartStereoProjectionFactorPP(model, smart_params)); - smartFactor3->add(measurements_l3, views, K2); + smartFactor3->add(measurements_l3, poseKeys, extrinsicKeys, K2); const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10); + // Values + Pose3 body_Pose_cam1 = Pose3(Rot3::Ypr(-M_PI, 1., 0.1),Point3(0, 1, 0)); + Pose3 body_Pose_cam2 = Pose3(Rot3::Ypr(-M_PI / 4, 0.1, 1.0),Point3(1, 1, 1)); + Pose3 body_Pose_cam3 = Pose3::identity(); + Pose3 w_Pose_body1 = w_Pose_cam1.compose(body_Pose_cam1.inverse()); + Pose3 w_Pose_body2 = w_Pose_cam2.compose(body_Pose_cam2.inverse()); + Pose3 w_Pose_body3 = w_Pose_cam3.compose(body_Pose_cam3.inverse()); + + Values values; + Pose3 noise_pose = Pose3(Rot3::Ypr(-M_PI / 100, 0., -M_PI / 100), Point3(0.1, 0.1, 0.1)); // smaller noise + values.insert(x1, w_Pose_body1); + values.insert(x2, w_Pose_body2); + values.insert(x3, w_Pose_body3); + values.insert(body_P_cam1_key, body_Pose_cam1); + values.insert(body_P_cam2_key, body_Pose_cam2); + // initialize third calibration with some noise, we expect it to move back to original pose3 + values.insert(body_P_cam3_key, body_Pose_cam3 * noise_pose); + + // Graph NonlinearFactorGraph graph; graph.push_back(smartFactor1); graph.push_back(smartFactor2); graph.push_back(smartFactor3); - graph.addPrior(x1, pose1, noisePrior); - graph.addPrior(x2, pose2, noisePrior); + graph.addPrior(x1, w_Pose_body1, noisePrior); + graph.addPrior(x2, w_Pose_body2, noisePrior); + graph.addPrior(x3, w_Pose_body3, noisePrior); + // we might need some prior on the calibration too + graph.addPrior(body_P_cam1_key, body_Pose_cam1, noisePrior); + graph.addPrior(body_P_cam2_key, body_Pose_cam2, 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, pose1); - values.insert(x2, pose2); - // initialize third pose with some noise, we expect it to move back to original pose3 - values.insert(x3, pose3 * 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(x3))); + Point3(0.1, -0.1, 1.9)), values.at(x3) * values.at(body_P_cam3_key))); // cout << std::setprecision(10) << "\n----SmartStereoFactor graph initial error: " << graph.error(values) << endl; EXPECT_DOUBLES_EQUAL(833953.92789459578, graph.error(values), 1e-7); // initial error - // get triangulated landmarks from smart factors - Point3 landmark1_smart = *smartFactor1->point(); - Point3 landmark2_smart = *smartFactor2->point(); - Point3 landmark3_smart = *smartFactor3->point(); +// // get triangulated landmarks from smart factors +// Point3 landmark1_smart = *smartFactor1->point(); +// Point3 landmark2_smart = *smartFactor2->point(); +// Point3 landmark3_smart = *smartFactor3->point(); +// +// Values result; +// gttic_(SmartStereoProjectionFactorPP); +// LevenbergMarquardtOptimizer optimizer(graph, values, lm_params); +// result = optimizer.optimize(); +// gttoc_(SmartStereoProjectionFactorPP); +// tictoc_finishedIteration_(); +// +// EXPECT_DOUBLES_EQUAL(0, graph.error(result), 1e-5); - Values result; - gttic_(SmartStereoProjectionFactorPP); - LevenbergMarquardtOptimizer optimizer(graph, values, lm_params); - result = optimizer.optimize(); - gttoc_(SmartStereoProjectionFactorPP); - tictoc_finishedIteration_(); - - EXPECT_DOUBLES_EQUAL(0, graph.error(result), 1e-5); - -// cout << std::setprecision(10) << "SmartStereoFactor graph optimized error: " << graph.error(result) << endl; - - GaussianFactorGraph::shared_ptr GFG = graph.linearize(result); - VectorValues delta = GFG->optimize(); - VectorValues expected = VectorValues::Zero(delta); - EXPECT(assert_equal(expected, delta, 1e-6)); - - // result.print("results of 3 camera, 3 landmark optimization \n"); - EXPECT(assert_equal(pose3, result.at(x3))); - - // *************************************************************** - // Same problem with regular Stereo factors, expect same error! - // **************************************************************** - -// landmark1_smart.print("landmark1_smart"); -// landmark2_smart.print("landmark2_smart"); -// landmark3_smart.print("landmark3_smart"); - - // add landmarks to values - values.insert(L(1), landmark1_smart); - values.insert(L(2), landmark2_smart); - values.insert(L(3), landmark3_smart); - - // add factors - NonlinearFactorGraph graph2; - - graph2.addPrior(x1, pose1, noisePrior); - graph2.addPrior(x2, pose2, noisePrior); - - typedef GenericStereoFactor ProjectionFactor; - - bool verboseCheirality = true; - - graph2.push_back(ProjectionFactor(measurements_l1[0], model, x1, L(1), K2, false, verboseCheirality)); - graph2.push_back(ProjectionFactor(measurements_l1[1], model, x2, L(1), K2, false, verboseCheirality)); - graph2.push_back(ProjectionFactor(measurements_l1[2], model, x3, L(1), K2, false, verboseCheirality)); - - graph2.push_back(ProjectionFactor(measurements_l2[0], model, x1, L(2), K2, false, verboseCheirality)); - graph2.push_back(ProjectionFactor(measurements_l2[1], model, x2, L(2), K2, false, verboseCheirality)); - graph2.push_back(ProjectionFactor(measurements_l2[2], model, x3, L(2), K2, false, verboseCheirality)); - - graph2.push_back(ProjectionFactor(measurements_l3[0], model, x1, L(3), K2, false, verboseCheirality)); - graph2.push_back(ProjectionFactor(measurements_l3[1], model, x2, L(3), K2, false, verboseCheirality)); - graph2.push_back(ProjectionFactor(measurements_l3[2], model, x3, L(3), K2, false, verboseCheirality)); - -// cout << std::setprecision(10) << "\n----StereoFactor graph initial error: " << graph2.error(values) << endl; - EXPECT_DOUBLES_EQUAL(833953.92789459578, graph2.error(values), 1e-7); - - LevenbergMarquardtOptimizer optimizer2(graph2, values, lm_params); - Values result2 = optimizer2.optimize(); - EXPECT_DOUBLES_EQUAL(0, graph2.error(result2), 1e-5); - -// cout << std::setprecision(10) << "StereoFactor graph optimized error: " << graph2.error(result2) << endl; +//// cout << std::setprecision(10) << "SmartStereoFactor graph optimized error: " << graph.error(result) << endl; +// +// GaussianFactorGraph::shared_ptr GFG = graph.linearize(result); +// VectorValues delta = GFG->optimize(); +// VectorValues expected = VectorValues::Zero(delta); +// EXPECT(assert_equal(expected, delta, 1e-6)); +// +// // result.print("results of 3 camera, 3 landmark optimization \n"); +// EXPECT(assert_equal(w_Pose_cam3, result.at(x3))); +// +// // *************************************************************** +// // Same problem with regular Stereo factors, expect same error! +// // **************************************************************** +// +//// landmark1_smart.print("landmark1_smart"); +//// landmark2_smart.print("landmark2_smart"); +//// landmark3_smart.print("landmark3_smart"); +// +// // add landmarks to values +// values.insert(L(1), landmark1_smart); +// values.insert(L(2), landmark2_smart); +// values.insert(L(3), landmark3_smart); +// +// // add factors +// NonlinearFactorGraph graph2; +// +// graph2.addPrior(x1, w_Pose_cam1, noisePrior); +// graph2.addPrior(x2, w_Pose_cam2, noisePrior); +// +// typedef GenericStereoFactor ProjectionFactor; +// +// bool verboseCheirality = true; +// +// graph2.push_back(ProjectionFactor(measurements_l1[0], model, x1, L(1), K2, false, verboseCheirality)); +// graph2.push_back(ProjectionFactor(measurements_l1[1], model, x2, L(1), K2, false, verboseCheirality)); +// graph2.push_back(ProjectionFactor(measurements_l1[2], model, x3, L(1), K2, false, verboseCheirality)); +// +// graph2.push_back(ProjectionFactor(measurements_l2[0], model, x1, L(2), K2, false, verboseCheirality)); +// graph2.push_back(ProjectionFactor(measurements_l2[1], model, x2, L(2), K2, false, verboseCheirality)); +// graph2.push_back(ProjectionFactor(measurements_l2[2], model, x3, L(2), K2, false, verboseCheirality)); +// +// graph2.push_back(ProjectionFactor(measurements_l3[0], model, x1, L(3), K2, false, verboseCheirality)); +// graph2.push_back(ProjectionFactor(measurements_l3[1], model, x2, L(3), K2, false, verboseCheirality)); +// graph2.push_back(ProjectionFactor(measurements_l3[2], model, x3, L(3), K2, false, verboseCheirality)); +// +//// cout << std::setprecision(10) << "\n----StereoFactor graph initial error: " << graph2.error(values) << endl; +// EXPECT_DOUBLES_EQUAL(833953.92789459578, graph2.error(values), 1e-7); +// +// LevenbergMarquardtOptimizer optimizer2(graph2, values, lm_params); +// Values result2 = optimizer2.optimize(); +// EXPECT_DOUBLES_EQUAL(0, graph2.error(result2), 1e-5); +// +//// cout << std::setprecision(10) << "StereoFactor graph optimized error: " << graph2.error(result2) << endl; } /* *************************************************************************