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release/4.3a0
lcarlone 2021-03-13 18:10:03 -05:00
parent 0194e3df94
commit c1da490c2d
1 changed files with 111 additions and 91 deletions
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202
gtsam_unstable/slam/tests/testSmartStereoProjectionFactorPP.cpp
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@ -366,20 +366,20 @@ TEST( SmartStereoProjectionFactorPP, noisy ) {
DOUBLES_EQUAL(actualError1, 5381978, 1); // value freeze DOUBLES_EQUAL(actualError1, 5381978, 1); // value freeze
} }
/* ************************************************************************* /* *************************************************************************/
TEST( SmartStereoProjectionFactorPP, 3poses_smart_projection_factor ) { TEST( SmartStereoProjectionFactorPP, 3poses_smart_projection_factor ) {
// create first camera. Looking along X-axis, 1 meter above ground plane (x-y) // 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)); Pose3 w_Pose_cam1 = Pose3(Rot3::Ypr(-M_PI / 2, 0., -M_PI / 2), Point3(0, 0, 1));
StereoCamera cam1(pose1, K2); StereoCamera cam1(w_Pose_cam1, K2);
// create second camera 1 meter to the right of first camera // create second camera 1 meter to the right of first camera
Pose3 pose2 = pose1 * Pose3(Rot3(), Point3(1, 0, 0)); Pose3 w_Pose_cam2 = w_Pose_cam1 * Pose3(Rot3(), Point3(1, 0, 0));
StereoCamera cam2(pose2, K2); StereoCamera cam2(w_Pose_cam2, K2);
// create third camera 1 meter above the first camera // create third camera 1 meter above the first camera
Pose3 pose3 = pose1 * Pose3(Rot3(), Point3(0, -1, 0)); Pose3 w_Pose_cam3 = w_Pose_cam1 * Pose3(Rot3(), Point3(0, -1, 0));
StereoCamera cam3(pose3, K2); StereoCamera cam3(w_Pose_cam3, K2);
// three landmarks ~5 meters infront of camera // three landmarks ~5 meters infront of camera
Point3 landmark1(5, 0.5, 1.2); Point3 landmark1(5, 0.5, 1.2);
@ -394,116 +394,136 @@ TEST( SmartStereoProjectionFactorPP, 3poses_smart_projection_factor ) {
vector<StereoPoint2> measurements_l3 = stereo_projectToMultipleCameras(cam1, vector<StereoPoint2> measurements_l3 = stereo_projectToMultipleCameras(cam1,
cam2, cam3, landmark3); cam2, cam3, landmark3);
KeyVector views; KeyVector poseKeys;
views.push_back(x1); poseKeys.push_back(x1);
views.push_back(x2); poseKeys.push_back(x2);
views.push_back(x3); 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; SmartStereoProjectionParams smart_params;
smart_params.triangulation.enableEPI = true; smart_params.triangulation.enableEPI = true;
SmartStereoProjectionFactorPP::shared_ptr smartFactor1(new SmartStereoProjectionFactorPP(model, smart_params)); 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)); 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)); 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); 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; NonlinearFactorGraph graph;
graph.push_back(smartFactor1); graph.push_back(smartFactor1);
graph.push_back(smartFactor2); graph.push_back(smartFactor2);
graph.push_back(smartFactor3); graph.push_back(smartFactor3);
graph.addPrior(x1, pose1, noisePrior); graph.addPrior(x1, w_Pose_body1, noisePrior);
graph.addPrior(x2, pose2, 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( EXPECT(
assert_equal( assert_equal(
Pose3( Pose3(
Rot3(0, -0.0314107591, 0.99950656, -0.99950656, -0.0313952598, Rot3(0, -0.0314107591, 0.99950656, -0.99950656, -0.0313952598,
-0.000986635786, 0.0314107591, -0.999013364, -0.0313952598), -0.000986635786, 0.0314107591, -0.999013364, -0.0313952598),
Point3(0.1, -0.1, 1.9)), values.at<Pose3>(x3))); Point3(0.1, -0.1, 1.9)), values.at<Pose3>(x3) * values.at<Pose3>(body_P_cam3_key)));
// cout << std::setprecision(10) << "\n----SmartStereoFactor graph initial error: " << graph.error(values) << endl; // 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 EXPECT_DOUBLES_EQUAL(833953.92789459578, graph.error(values), 1e-7); // initial error
// get triangulated landmarks from smart factors // // get triangulated landmarks from smart factors
Point3 landmark1_smart = *smartFactor1->point(); // Point3 landmark1_smart = *smartFactor1->point();
Point3 landmark2_smart = *smartFactor2->point(); // Point3 landmark2_smart = *smartFactor2->point();
Point3 landmark3_smart = *smartFactor3->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; //// cout << std::setprecision(10) << "SmartStereoFactor graph optimized error: " << graph.error(result) << endl;
gttic_(SmartStereoProjectionFactorPP); //
LevenbergMarquardtOptimizer optimizer(graph, values, lm_params); // GaussianFactorGraph::shared_ptr GFG = graph.linearize(result);
result = optimizer.optimize(); // VectorValues delta = GFG->optimize();
gttoc_(SmartStereoProjectionFactorPP); // VectorValues expected = VectorValues::Zero(delta);
tictoc_finishedIteration_(); // EXPECT(assert_equal(expected, delta, 1e-6));
//
EXPECT_DOUBLES_EQUAL(0, graph.error(result), 1e-5); // // result.print("results of 3 camera, 3 landmark optimization \n");
// EXPECT(assert_equal(w_Pose_cam3, result.at<Pose3>(x3)));
// cout << std::setprecision(10) << "SmartStereoFactor graph optimized error: " << graph.error(result) << endl; //
// // ***************************************************************
GaussianFactorGraph::shared_ptr GFG = graph.linearize(result); // // Same problem with regular Stereo factors, expect same error!
VectorValues delta = GFG->optimize(); // // ****************************************************************
VectorValues expected = VectorValues::Zero(delta); //
EXPECT(assert_equal(expected, delta, 1e-6)); //// landmark1_smart.print("landmark1_smart");
//// landmark2_smart.print("landmark2_smart");
// result.print("results of 3 camera, 3 landmark optimization \n"); //// landmark3_smart.print("landmark3_smart");
EXPECT(assert_equal(pose3, result.at<Pose3>(x3))); //
// // add landmarks to values
// *************************************************************** // values.insert(L(1), landmark1_smart);
// Same problem with regular Stereo factors, expect same error! // values.insert(L(2), landmark2_smart);
// **************************************************************** // values.insert(L(3), landmark3_smart);
//
// landmark1_smart.print("landmark1_smart"); // // add factors
// landmark2_smart.print("landmark2_smart"); // NonlinearFactorGraph graph2;
// landmark3_smart.print("landmark3_smart"); //
// graph2.addPrior(x1, w_Pose_cam1, noisePrior);
// add landmarks to values // graph2.addPrior(x2, w_Pose_cam2, noisePrior);
values.insert(L(1), landmark1_smart); //
values.insert(L(2), landmark2_smart); // typedef GenericStereoFactor<Pose3, Point3> ProjectionFactor;
values.insert(L(3), landmark3_smart); //
// bool verboseCheirality = true;
// add factors //
NonlinearFactorGraph graph2; // 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.addPrior(x1, pose1, noisePrior); // graph2.push_back(ProjectionFactor(measurements_l1[2], model, x3, L(1), K2, false, verboseCheirality));
graph2.addPrior(x2, pose2, noisePrior); //
// graph2.push_back(ProjectionFactor(measurements_l2[0], model, x1, L(2), K2, false, verboseCheirality));
typedef GenericStereoFactor<Pose3, Point3> ProjectionFactor; // 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));
bool verboseCheirality = true; //
// graph2.push_back(ProjectionFactor(measurements_l3[0], model, x1, L(3), K2, false, verboseCheirality));
graph2.push_back(ProjectionFactor(measurements_l1[0], model, x1, L(1), K2, false, verboseCheirality)); // graph2.push_back(ProjectionFactor(measurements_l3[1], model, x2, L(3), K2, false, verboseCheirality));
graph2.push_back(ProjectionFactor(measurements_l1[1], model, x2, L(1), K2, false, verboseCheirality)); // graph2.push_back(ProjectionFactor(measurements_l3[2], model, x3, L(3), K2, false, verboseCheirality));
graph2.push_back(ProjectionFactor(measurements_l1[2], model, x3, L(1), K2, false, verboseCheirality)); //
//// cout << std::setprecision(10) << "\n----StereoFactor graph initial error: " << graph2.error(values) << endl;
graph2.push_back(ProjectionFactor(measurements_l2[0], model, x1, L(2), K2, false, verboseCheirality)); // EXPECT_DOUBLES_EQUAL(833953.92789459578, graph2.error(values), 1e-7);
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)); // LevenbergMarquardtOptimizer optimizer2(graph2, values, lm_params);
// Values result2 = optimizer2.optimize();
graph2.push_back(ProjectionFactor(measurements_l3[0], model, x1, L(3), K2, false, verboseCheirality)); // EXPECT_DOUBLES_EQUAL(0, graph2.error(result2), 1e-5);
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) << "StereoFactor graph optimized error: " << graph2.error(result2) << endl;
// 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;
} }
/* ************************************************************************* /* *************************************************************************