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adding test with regular projection factors for comparison, and bug fixes in SmartFactor test.

release/4.3a0
Chris Beall 2013-08-05 17:58:32 +00:00
parent 587bfd3772
commit 5518007317
1 changed files with 80 additions and 151 deletions
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231
gtsam_unstable/slam/tests/testSmartProjectionFactor.cpp
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@ -53,13 +53,13 @@ static Cal3_S2::shared_ptr K(new Cal3_S2(fov,w,h));
static SharedNoiseModel model(noiseModel::Unit::Create(2));
// Convenience for named keys
//using symbol_shorthand::X;
//using symbol_shorthand::L;
using symbol_shorthand::X;
using symbol_shorthand::L;
//typedef GenericProjectionFactor<Pose3, Point3> TestProjectionFactor;
///* ************************************************************************* */
/* ************************************************************************* *
TEST( MultiProjectionFactor, noiseless ){
cout << " ************************ MultiProjectionFactor: noiseless ****************************" << endl;
Values theta;
@ -106,7 +106,7 @@ TEST( MultiProjectionFactor, noiseless ){
DOUBLES_EQUAL(expectedError, actualError, 1e-7);
}
///* ************************************************************************* */
/* ************************************************************************* *
TEST( MultiProjectionFactor, noisy ){
cout << " ************************ MultiProjectionFactor: noisy ****************************" << endl;
@ -157,7 +157,7 @@ TEST( MultiProjectionFactor, noisy ){
}
///* ************************************************************************* */
/* ************************************************************************* */
TEST( MultiProjectionFactor, 3poses ){
cout << " ************************ MultiProjectionFactor: 3 cams + 3 landmarks **********************" << endl;
@ -181,12 +181,12 @@ TEST( MultiProjectionFactor, 3poses ){
// create third camera 1 meter above the first camera
Pose3 pose3 = pose1 * Pose3(Rot3(), Point3(0,-1,0));
SimpleCamera cam3(pose2, *K);
SimpleCamera cam3(pose3, *K);
// three landmarks ~5 meters infront of camera
Point3 landmark1(5, 0.5, 1.2);
Point3 landmark2(5, -0.5, 1.2);
Point3 landmark3(5, 0, 3.0);
Point3 landmark3(3, 0, 3.0);
vector<Point2> measurements_cam1, measurements_cam2, measurements_cam3;
@ -224,12 +224,13 @@ TEST( MultiProjectionFactor, 3poses ){
graph.push_back(smartFactor2);
graph.push_back(smartFactor3);
graph.add(PriorFactor<Pose3>(x1, pose1, noisePrior));
graph.add(PriorFactor<Pose3>(x2, pose2, noisePrior));
Pose3 noise_pose = Pose3(Rot3::ypr(-M_PI/10, 0., -M_PI/10), gtsam::Point3(0.5,0.1,0.3));
Values values;
values.insert(x1, pose1);
values.insert(x2, pose1);
values.insert(x2, pose2);
values.insert(x3, pose3* noise_pose);
LevenbergMarquardtParams params;
@ -244,149 +245,77 @@ TEST( MultiProjectionFactor, 3poses ){
///* ************************************************************************* */
//TEST( ProjectionFactor, nonStandard ) {
// GenericProjectionFactor<Pose3, Point3, Cal3DS2> f;
//}
//
///* ************************************************************************* */
//TEST( ProjectionFactor, Constructor) {
// Key poseKey(X(1));
// Key pointKey(L(1));
//
// Point2 measurement(323.0, 240.0);
//
// TestProjectionFactor factor(measurement, model, poseKey, pointKey, K);
//}
//
///* ************************************************************************* */
//TEST( ProjectionFactor, ConstructorWithTransform) {
// Key poseKey(X(1));
// Key pointKey(L(1));
//
// Point2 measurement(323.0, 240.0);
// Pose3 body_P_sensor(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
//
// TestProjectionFactor factor(measurement, model, poseKey, pointKey, K, body_P_sensor);
//}
//
///* ************************************************************************* */
//TEST( ProjectionFactor, Equals ) {
// // Create two identical factors and make sure they're equal
// Point2 measurement(323.0, 240.0);
//
// TestProjectionFactor factor1(measurement, model, X(1), L(1), K);
// TestProjectionFactor factor2(measurement, model, X(1), L(1), K);
//
// CHECK(assert_equal(factor1, factor2));
//}
//
///* ************************************************************************* */
//TEST( ProjectionFactor, EqualsWithTransform ) {
// // Create two identical factors and make sure they're equal
// Point2 measurement(323.0, 240.0);
// Pose3 body_P_sensor(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
//
// TestProjectionFactor factor1(measurement, model, X(1), L(1), K, body_P_sensor);
// TestProjectionFactor factor2(measurement, model, X(1), L(1), K, body_P_sensor);
//
// CHECK(assert_equal(factor1, factor2));
//}
//
///* ************************************************************************* */
//TEST( ProjectionFactor, Error ) {
// // Create the factor with a measurement that is 3 pixels off in x
// Key poseKey(X(1));
// Key pointKey(L(1));
// Point2 measurement(323.0, 240.0);
// TestProjectionFactor factor(measurement, model, poseKey, pointKey, K);
//
// // Set the linearization point
// Pose3 pose(Rot3(), Point3(0,0,-6));
// Point3 point(0.0, 0.0, 0.0);
//
// // Use the factor to calculate the error
// Vector actualError(factor.evaluateError(pose, point));
//
// // The expected error is (-3.0, 0.0) pixels / UnitCovariance
// Vector expectedError = Vector_(2, -3.0, 0.0);
//
// // Verify we get the expected error
// CHECK(assert_equal(expectedError, actualError, 1e-9));
//}
//
///* ************************************************************************* */
//TEST( ProjectionFactor, ErrorWithTransform ) {
// // Create the factor with a measurement that is 3 pixels off in x
// Key poseKey(X(1));
// Key pointKey(L(1));
// Point2 measurement(323.0, 240.0);
// Pose3 body_P_sensor(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
// TestProjectionFactor factor(measurement, model, poseKey, pointKey, K, body_P_sensor);
//
// // Set the linearization point. The vehicle pose has been selected to put the camera at (-6, 0, 0)
// Pose3 pose(Rot3(), Point3(-6.25, 0.10 , -1.0));
// Point3 point(0.0, 0.0, 0.0);
//
// // Use the factor to calculate the error
// Vector actualError(factor.evaluateError(pose, point));
//
// // The expected error is (-3.0, 0.0) pixels / UnitCovariance
// Vector expectedError = Vector_(2, -3.0, 0.0);
//
// // Verify we get the expected error
// CHECK(assert_equal(expectedError, actualError, 1e-9));
//}
//
///* ************************************************************************* */
//TEST( ProjectionFactor, Jacobian ) {
// // Create the factor with a measurement that is 3 pixels off in x
// Key poseKey(X(1));
// Key pointKey(L(1));
// Point2 measurement(323.0, 240.0);
// TestProjectionFactor factor(measurement, model, poseKey, pointKey, K);
//
// // Set the linearization point
// Pose3 pose(Rot3(), Point3(0,0,-6));
// Point3 point(0.0, 0.0, 0.0);
//
// // Use the factor to calculate the Jacobians
// Matrix H1Actual, H2Actual;
// factor.evaluateError(pose, point, H1Actual, H2Actual);
//
// // The expected Jacobians
// Matrix H1Expected = Matrix_(2, 6, 0., -554.256, 0., -92.376, 0., 0., 554.256, 0., 0., 0., -92.376, 0.);
// Matrix H2Expected = Matrix_(2, 3, 92.376, 0., 0., 0., 92.376, 0.);
//
// // Verify the Jacobians are correct
// CHECK(assert_equal(H1Expected, H1Actual, 1e-3));
// CHECK(assert_equal(H2Expected, H2Actual, 1e-3));
//}
//
///* ************************************************************************* */
//TEST( ProjectionFactor, JacobianWithTransform ) {
// // Create the factor with a measurement that is 3 pixels off in x
// Key poseKey(X(1));
// Key pointKey(L(1));
// Point2 measurement(323.0, 240.0);
// Pose3 body_P_sensor(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
// TestProjectionFactor factor(measurement, model, poseKey, pointKey, K, body_P_sensor);
//
// // Set the linearization point. The vehicle pose has been selected to put the camera at (-6, 0, 0)
// Pose3 pose(Rot3(), Point3(-6.25, 0.10 , -1.0));
// Point3 point(0.0, 0.0, 0.0);
//
// // Use the factor to calculate the Jacobians
// Matrix H1Actual, H2Actual;
// factor.evaluateError(pose, point, H1Actual, H2Actual);
//
// // The expected Jacobians
// Matrix H1Expected = Matrix_(2, 6, -92.376, 0., 577.350, 0., 92.376, 0., -9.2376, -577.350, 0., 0., 0., 92.376);
// Matrix H2Expected = Matrix_(2, 3, 0., -92.376, 0., 0., 0., -92.376);
//
// // Verify the Jacobians are correct
// CHECK(assert_equal(H1Expected, H1Actual, 1e-3));
// CHECK(assert_equal(H2Expected, H2Actual, 1e-3));
//}
TEST( MultiProjectionFactor, 3poses_projection_factor ){
cout << " ************************ Normal ProjectionFactor: 3 cams + 3 landmarks **********************" << endl;
Symbol x1('X', 1);
Symbol x2('X', 2);
Symbol x3('X', 3);
const SharedDiagonal noiseProjection = noiseModel::Isotropic::Sigma(2, 1);
std::vector<Key> views;
views += x1, x2, x3;
Cal3_S2::shared_ptr K(new Cal3_S2(1500, 1200, 0, 640, 480));
// 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), gtsam::Point3(0,0,1));
SimpleCamera cam1(pose1, *K);
// create second camera 1 meter to the right of first camera
Pose3 pose2 = pose1 * Pose3(Rot3(), Point3(1,0,0));
SimpleCamera cam2(pose2, *K);
// create third camera 1 meter above the first camera
Pose3 pose3 = pose1 * Pose3(Rot3(), Point3(0,-1,0));
pose3.print("Pose3: ");
SimpleCamera cam3(pose3, *K);
// three landmarks ~5 meters infront of camera
Point3 landmark1(5, 0.5, 1.2);
Point3 landmark2(5, -0.5, 1.2);
Point3 landmark3(3, 0, 3.0);
typedef GenericProjectionFactor<Pose3, Point3> ProjectionFactor;
NonlinearFactorGraph graph;
// 1. Project three landmarks into three cameras and triangulate
graph.add(ProjectionFactor(cam1.project(landmark1), noiseProjection, x1, L(1), K));
graph.add(ProjectionFactor(cam2.project(landmark1), noiseProjection, x2, L(1), K));
graph.add(ProjectionFactor(cam3.project(landmark1), noiseProjection, x3, L(1), K));
//
graph.add(ProjectionFactor(cam1.project(landmark2), noiseProjection, x1, L(2), K));
graph.add(ProjectionFactor(cam2.project(landmark2), noiseProjection, x2, L(2), K));
graph.add(ProjectionFactor(cam3.project(landmark2), noiseProjection, x3, L(2), K));
graph.add(ProjectionFactor(cam1.project(landmark3), noiseProjection, x1, L(3), K));
graph.add(ProjectionFactor(cam2.project(landmark3), noiseProjection, x2, L(3), K));
graph.add(ProjectionFactor(cam3.project(landmark3), noiseProjection, x3, L(3), K));
const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
graph.add(PriorFactor<Pose3>(x1, pose1, noisePrior));
graph.add(PriorFactor<Pose3>(x2, pose2, noisePrior));
Pose3 noise_pose = Pose3(Rot3::ypr(-M_PI/10, 0., -M_PI/10), gtsam::Point3(0.5,0.1,0.3));
Values values;
values.insert(x1, pose1);
values.insert(x2, pose2);
values.insert(x3, pose3* noise_pose);
values.insert(L(1), landmark1);
values.insert(L(2), landmark2);
values.insert(L(3), landmark3);
LevenbergMarquardtParams params;
// params.verbosityLM = LevenbergMarquardtParams::TRYLAMBDA;
// params.verbosity = NonlinearOptimizerParams::ERROR;
LevenbergMarquardtOptimizer optimizer(graph, values, params);
Values result = optimizer.optimize();
result.print("Regular Projection Factor: results of 3 camera, 3 landmark optimization \n");
}
/* ************************************************************************* */
int main() { TestResult tr; return TestRegistry::runAllTests(tr); }