219 lines
8.1 KiB
C++
219 lines
8.1 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file testStereoFactor.cpp
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* @brief Unit test for StereoFactor
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* @author Chris Beall
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*/
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#include <gtsam/slam/StereoFactor.h>
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#include <gtsam/nonlinear/NonlinearEquality.h>
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#include <gtsam/nonlinear/GaussNewtonOptimizer.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/geometry/StereoCamera.h>
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#include <gtsam/geometry/Cal3_S2Stereo.h>
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#include <gtsam/geometry/Pose3.h>
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#include <gtsam/geometry/Point3.h>
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#include <CppUnitLite/TestHarness.h>
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using namespace std;
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using namespace gtsam;
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static Pose3 camera1(Rot3(Vector3(1, -1, -1).asDiagonal()),
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Point3(0,0,6.25));
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static boost::shared_ptr<Cal3_S2Stereo> K(new Cal3_S2Stereo(625, 625, 0, 320, 240, 0.5));
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// point X Y Z in meters
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static Point3 p(0, 0, 5);
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static SharedNoiseModel model(noiseModel::Unit::Create(3));
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// Convenience for named keys
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using symbol_shorthand::X;
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using symbol_shorthand::L;
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typedef GenericStereoFactor<Pose3, Point3> TestStereoFactor;
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/* ************************************************************************* */
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TEST( StereoFactor, Constructor) {
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StereoPoint2 measurement(323, 318-50, 241);
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TestStereoFactor factor(measurement, model, X(1), L(1), K);
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}
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/* ************************************************************************* */
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TEST( StereoFactor, ConstructorWithTransform) {
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StereoPoint2 measurement(323, 318-50, 241);
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Pose3 body_P_sensor(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
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TestStereoFactor factor(measurement, model, X(1), L(1), K, body_P_sensor);
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}
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/* ************************************************************************* */
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TEST( StereoFactor, Equals ) {
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// Create two identical factors and make sure they're equal
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StereoPoint2 measurement(323, 318-50, 241);
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TestStereoFactor factor1(measurement, model, X(1), L(1), K);
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TestStereoFactor factor2(measurement, model, X(1), L(1), K);
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CHECK(assert_equal(factor1, factor2));
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}
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/* ************************************************************************* */
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TEST( StereoFactor, EqualsWithTransform ) {
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// Create two identical factors and make sure they're equal
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StereoPoint2 measurement(323, 318-50, 241);
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Pose3 body_P_sensor(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
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TestStereoFactor factor1(measurement, model, X(1), L(1), K, body_P_sensor);
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TestStereoFactor factor2(measurement, model, X(1), L(1), K, body_P_sensor);
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CHECK(assert_equal(factor1, factor2));
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}
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/* ************************************************************************* */
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TEST( StereoFactor, Error ) {
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// Create the factor with a measurement that is 3 pixels off in x
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StereoPoint2 measurement(323, 318-50, 241);
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TestStereoFactor factor(measurement, model, X(1), L(1), K);
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// Set the linearization point
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Pose3 pose(Rot3(), Point3(0.0, 0.0, -6.25));
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Point3 point(0.0, 0.0, 0.0);
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// Use the factor to calculate the error
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Vector actualError(factor.evaluateError(pose, point));
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// The expected error is (-3.0, +2.0, -1.0) pixels / UnitCovariance
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Vector expectedError = Vector3(-3.0, +2.0, -1.0);
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// Verify we get the expected error
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CHECK(assert_equal(expectedError, actualError, 1e-9));
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}
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/* ************************************************************************* */
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TEST( StereoFactor, ErrorWithTransform ) {
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// Create the factor with a measurement that is 3 pixels off in x
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StereoPoint2 measurement(323, 318-50, 241);
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Pose3 body_P_sensor(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
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TestStereoFactor factor(measurement, model, X(1), L(1), K, body_P_sensor);
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// Set the linearization point. The vehicle pose has been selected to put the camera at (-6, 0, 0)
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Pose3 pose(Rot3(), Point3(-6.50, 0.10 , -1.0));
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Point3 point(0.0, 0.0, 0.0);
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// Use the factor to calculate the error
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Vector actualError(factor.evaluateError(pose, point));
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// The expected error is (-3.0, +2.0, -1.0) pixels / UnitCovariance
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Vector expectedError = Vector3(-3.0, +2.0, -1.0);
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// Verify we get the expected error
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CHECK(assert_equal(expectedError, actualError, 1e-9));
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}
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/* ************************************************************************* */
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TEST( StereoFactor, Jacobian ) {
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// Create the factor with a measurement that is 3 pixels off in x
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StereoPoint2 measurement(323, 318-50, 241);
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TestStereoFactor factor(measurement, model, X(1), L(1), K);
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// Set the linearization point
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Pose3 pose(Rot3(), Point3(0.0, 0.0, -6.25));
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Point3 point(0.0, 0.0, 0.0);
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// Use the factor to calculate the Jacobians
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Matrix H1Actual, H2Actual;
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factor.evaluateError(pose, point, H1Actual, H2Actual);
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// The expected Jacobians
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Matrix H1Expected = (Matrix(3, 6) << 0.0, -625.0, 0.0, -100.0, 0.0, 0.0,
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0.0, -625.0, 0.0, -100.0, 0.0, -8.0,
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625.0, 0.0, 0.0, 0.0, -100.0, 0.0).finished();
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Matrix H2Expected = (Matrix(3, 3) << 100.0, 0.0, 0.0,
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100.0, 0.0, 8.0,
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0.0, 100.0, 0.0).finished();
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// Verify the Jacobians are correct
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CHECK(assert_equal(H1Expected, H1Actual, 1e-3));
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CHECK(assert_equal(H2Expected, H2Actual, 1e-3));
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}
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/* ************************************************************************* */
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TEST( StereoFactor, JacobianWithTransform ) {
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// Create the factor with a measurement that is 3 pixels off in x
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StereoPoint2 measurement(323, 318-50, 241);
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Pose3 body_P_sensor(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
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TestStereoFactor factor(measurement, model, X(1), L(1), K, body_P_sensor);
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// Set the linearization point. The vehicle pose has been selected to put the camera at (-6, 0, 0)
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Pose3 pose(Rot3(), Point3(-6.50, 0.10 , -1.0));
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Point3 point(0.0, 0.0, 0.0);
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// Use the factor to calculate the Jacobians
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Matrix H1Actual, H2Actual;
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factor.evaluateError(pose, point, H1Actual, H2Actual);
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// The expected Jacobians
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Matrix H1Expected = (Matrix(3, 6) << -100.0, 0.0, 650.0, 0.0, 100.0, 0.0,
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-100.0, -8.0, 649.2, -8.0, 100.0, 0.0,
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-10.0, -650.0, 0.0, 0.0, 0.0, 100.0).finished();
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Matrix H2Expected = (Matrix(3, 3) << 0.0, -100.0, 0.0,
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8.0, -100.0, 0.0,
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0.0, 0.0, -100.0).finished();
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// Verify the Jacobians are correct
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CHECK(assert_equal(H1Expected, H1Actual, 1e-3));
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CHECK(assert_equal(H2Expected, H2Actual, 1e-3));
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}
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/* ************************************************************************* */
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TEST( StereoFactor, singlePoint)
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{
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NonlinearFactorGraph graph;
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graph.emplace_shared<NonlinearEquality<Pose3> >(X(1), camera1);
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StereoPoint2 measurement(320, 320.0-50, 240);
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// arguments: measurement, sigma, cam#, measurement #, K, baseline (m)
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graph.emplace_shared<GenericStereoFactor<Pose3, Point3> >(measurement, model, X(1), L(1), K);
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// Create a configuration corresponding to the ground truth
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Values values;
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values.insert(X(1), camera1); // add camera at z=6.25m looking towards origin
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Point3 l1(0, 0, 0);
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values.insert(L(1), l1); // add point at origin;
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GaussNewtonOptimizer optimizer(graph, values);
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// We expect the initial to be zero because config is the ground truth
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DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9);
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// Iterate once, and the config should not have changed
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optimizer.iterate();
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DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9);
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// Complete solution
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optimizer.optimize();
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DOUBLES_EQUAL(0.0, optimizer.error(), 1e-6);
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}
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/* ************************************************************************* */
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int main() { TestResult tr; return TestRegistry::runAllTests(tr);}
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/* ************************************************************************* */
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