trying to fix crucial test
lcarlone
parent
483a1995ba
commit
7a30d8b4d4
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@ -103,11 +103,11 @@ double SmartStereoProjectionFactorPP::error(const Values& values) const {
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SmartStereoProjectionFactorPP::Base::Cameras
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SmartStereoProjectionFactorPP::cameras(const Values& values) const {
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assert(keys_.size() == K_all_.size());
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assert(keys_.size() == body_P_cam_keys_.size());
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assert(w_P_body_keys_.size() == K_all_.size());
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assert(w_P_body_keys_.size() == body_P_cam_keys_.size());
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Base::Cameras cameras;
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for (size_t i = 0; i < keys_.size(); i++) {
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Pose3 w_P_body = values.at<Pose3>(keys_[i]);
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for (size_t i = 0; i < w_P_body_keys_.size(); i++) {
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Pose3 w_P_body = values.at<Pose3>(w_P_body_keys_[i]);
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Pose3 body_P_cam = values.at<Pose3>(body_P_cam_keys_[i]);
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Pose3 w_P_cam = w_P_body.compose(body_P_cam);
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cameras.push_back(StereoCamera(w_P_cam, K_all_[i]));
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@ -18,6 +18,7 @@
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#include <gtsam/slam/tests/smartFactorScenarios.h>
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#include <gtsam_unstable/slam/SmartStereoProjectionFactorPP.h>
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#include <gtsam_unstable/slam/ProjectionFactorPPP.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/slam/PoseTranslationPrior.h>
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#include <gtsam/slam/ProjectionFactor.h>
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@ -455,76 +456,76 @@ TEST( SmartStereoProjectionFactorPP, 3poses_smart_projection_factor ) {
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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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EXPECT_DOUBLES_EQUAL(833953.92789459578, graph.error(values), 1e-7); // initial error (note - this also matches error below)
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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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// cost is large before optimization
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EXPECT_DOUBLES_EQUAL(833953.92789459461, graph.error(values), 1e-5);
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Values result;
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gttic_(SmartStereoProjectionFactorPP);
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graph.print("/n ==== /n");
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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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// // cout << std::setprecision(10) << "SmartStereoFactor graph optimized error: " << graph.error(result) << endl;
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// EXPECT_DOUBLES_EQUAL(0, graph.error(result), 1e-5);
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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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// 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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// cout << std::setprecision(10) << "SmartStereoFactor graph optimized error: " << graph.error(result) << endl;
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EXPECT_DOUBLES_EQUAL(0, graph.error(result), 1e-5);
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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(body_Pose_cam3, result.at<Pose3>(body_P_cam3_key)));
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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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// 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, w_Pose_body1, noisePrior);
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graph2.addPrior(x2, w_Pose_body2, noisePrior);
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graph2.addPrior(x3, w_Pose_body3, noisePrior);
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// we might need some prior on the calibration too
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graph2.addPrior(body_P_cam1_key, body_Pose_cam1, noisePrior);
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graph2.addPrior(body_P_cam2_key, body_Pose_cam2, noisePrior);
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typedef ProjectionFactorPPP<Pose3, Point3, Cal3_S2Stereo> ProjectionFactorPPP;
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bool verboseCheirality = true;
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graph2.push_back(ProjectionFactorPPP(measurements_l1[0], model, x1, body_P_cam1_key, L(1), K2));
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graph2.push_back(ProjectionFactorPPP(measurements_l1[1], model, x2, body_P_cam2_key, L(1), K2));
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graph2.push_back(ProjectionFactorPPP(measurements_l1[2], model, x3, body_P_cam3_key, L(1), K2));
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graph2.push_back(ProjectionFactorPPP(measurements_l2[0], model, x1, body_P_cam1_key, L(2), K2));
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graph2.push_back(ProjectionFactorPPP(measurements_l2[1], model, x2, body_P_cam2_key, L(2), K2));
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graph2.push_back(ProjectionFactorPPP(measurements_l2[2], model, x3, body_P_cam3_key, L(2), K2));
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graph2.push_back(ProjectionFactorPPP(measurements_l3[0], model, x1, body_P_cam1_key, L(3), K2));
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graph2.push_back(ProjectionFactorPPP(measurements_l3[1], model, x2, body_P_cam2_key, L(3), K2));
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graph2.push_back(ProjectionFactorPPP(measurements_l3[2], model, x3, body_P_cam3_key, L(3), K2));
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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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}
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/* *************************************************************************
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TEST( SmartStereoProjectionFactorPP, body_P_sensor ) {
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