234 lines
8.4 KiB
C++
234 lines
8.4 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 testProjectionFactor.cpp
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* @brief Unit tests for ProjectionFactorPPP Class
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* @author Chris Beall
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* @date July 2014
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*/
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#include <gtsam/base/numericalDerivative.h>
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#include <gtsam/base/TestableAssertions.h>
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#include <gtsam_unstable/slam/ProjectionFactorPPP.h>
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/geometry/Cal3DS2.h>
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#include <gtsam/geometry/Cal3_S2.h>
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#include <gtsam/geometry/Pose3.h>
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#include <gtsam/geometry/Point3.h>
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#include <gtsam/geometry/Point2.h>
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#include <CppUnitLite/TestHarness.h>
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using namespace std::placeholders;
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using namespace std;
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using namespace gtsam;
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// make a realistic calibration matrix
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static double fov = 60; // degrees
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static size_t w=640,h=480;
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static Cal3_S2::shared_ptr K(new Cal3_S2(fov,w,h));
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// Create a noise model for the pixel error
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static SharedNoiseModel model(noiseModel::Unit::Create(2));
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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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using symbol_shorthand::T;
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typedef ProjectionFactorPPP<Pose3, Point3> TestProjectionFactor;
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/// traits
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namespace gtsam {
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template<>
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struct traits<TestProjectionFactor> : public Testable<TestProjectionFactor> {
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};
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}
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/* ************************************************************************* */
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TEST( ProjectionFactorPPP, nonStandard ) {
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ProjectionFactorPPP<Pose3, Point3, Cal3DS2> f;
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}
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/* ************************************************************************* */
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TEST( ProjectionFactorPPP, Constructor) {
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Key poseKey(X(1));
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Key transformKey(T(1));
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Key pointKey(L(1));
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Point2 measurement(323.0, 240.0);
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TestProjectionFactor factor(measurement, model, poseKey, transformKey, pointKey, K);
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}
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/* ************************************************************************* */
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TEST( ProjectionFactorPPP, ConstructorWithTransform) {
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Key poseKey(X(1));
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Key transformKey(T(1));
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Key pointKey(L(1));
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Point2 measurement(323.0, 240.0);
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TestProjectionFactor factor(measurement, model, poseKey, transformKey, pointKey, K);
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}
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/* ************************************************************************* */
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TEST( ProjectionFactorPPP, Equals ) {
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// Create two identical factors and make sure they're equal
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Point2 measurement(323.0, 240.0);
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TestProjectionFactor factor1(measurement, model, X(1), T(1), L(1), K);
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TestProjectionFactor factor2(measurement, model, X(1), T(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( ProjectionFactorPPP, EqualsWithTransform ) {
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// Create two identical factors and make sure they're equal
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Point2 measurement(323.0, 240.0);
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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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TestProjectionFactor factor1(measurement, model, X(1), T(1), L(1), K);
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TestProjectionFactor factor2(measurement, model, X(1), T(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( ProjectionFactorPPP, Error ) {
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// Create the factor with a measurement that is 3 pixels off in x
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Key poseKey(X(1));
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Key transformKey(T(1));
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Key pointKey(L(1));
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Point2 measurement(323.0, 240.0);
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TestProjectionFactor factor(measurement, model, poseKey, transformKey, pointKey, K);
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// Set the linearization point
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Pose3 pose(Rot3(), Point3(0,0,-6));
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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, Pose3(), point));
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// The expected error is (-3.0, 0.0) pixels / UnitCovariance
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Vector expectedError = Vector2(-3.0, 0.0);
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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( ProjectionFactorPPP, ErrorWithTransform ) {
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// Create the factor with a measurement that is 3 pixels off in x
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Key poseKey(X(1));
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Key transformKey(T(1));
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Key pointKey(L(1));
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Point2 measurement(323.0, 240.0);
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Pose3 transform(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
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TestProjectionFactor factor(measurement, model, poseKey,transformKey, pointKey, K);
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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(-6.25, 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, transform, point));
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// The expected error is (-3.0, 0.0) pixels / UnitCovariance
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Vector expectedError = Vector2(-3.0, 0.0);
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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( ProjectionFactorPPP, Jacobian ) {
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// Create the factor with a measurement that is 3 pixels off in x
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Key poseKey(X(1));
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Key transformKey(T(1));
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Key pointKey(L(1));
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Point2 measurement(323.0, 240.0);
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TestProjectionFactor factor(measurement, model, poseKey, transformKey, pointKey, K);
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// Set the linearization point
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Pose3 pose(Rot3(), Point3(0,0,-6));
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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, H3Actual;
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factor.evaluateError(pose, Pose3(), point, H1Actual, H2Actual, H3Actual);
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// The expected Jacobians
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Matrix H1Expected = (Matrix(2, 6) << 0., -554.256, 0., -92.376, 0., 0., 554.256, 0., 0., 0., -92.376, 0.).finished();
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Matrix H3Expected = (Matrix(2, 3) << 92.376, 0., 0., 0., 92.376, 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(H3Expected, H3Actual, 1e-3));
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// Verify H2 with numerical derivative
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Matrix H2Expected = numericalDerivative32<Vector, Pose3, Pose3, Point3>(
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std::function<Vector(const Pose3&, const Pose3&, const Point3&)>(
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std::bind(&TestProjectionFactor::evaluateError, &factor,
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std::placeholders::_1, std::placeholders::_2,
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std::placeholders::_3, boost::none, boost::none,
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boost::none)),
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pose, Pose3(), point);
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CHECK(assert_equal(H2Expected, H2Actual, 1e-5));
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}
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/* ************************************************************************* */
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TEST( ProjectionFactorPPP, JacobianWithTransform ) {
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// Create the factor with a measurement that is 3 pixels off in x
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Key poseKey(X(1));
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Key transformKey(T(1));
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Key pointKey(L(1));
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Point2 measurement(323.0, 240.0);
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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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TestProjectionFactor factor(measurement, model, poseKey, transformKey, pointKey, K);
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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(-6.25, 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, H3Actual;
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factor.evaluateError(pose, body_P_sensor, point, H1Actual, H2Actual, H3Actual);
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// The expected Jacobians
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Matrix H1Expected = (Matrix(2, 6) << -92.376, 0., 577.350, 0., 92.376, 0., -9.2376, -577.350, 0., 0., 0., 92.376).finished();
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Matrix H3Expected = (Matrix(2, 3) << 0., -92.376, 0., 0., 0., -92.376).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(H3Expected, H3Actual, 1e-3));
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// Verify H2 with numerical derivative
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Matrix H2Expected = numericalDerivative32<Vector, Pose3, Pose3, Point3>(
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std::function<Vector(const Pose3&, const Pose3&, const Point3&)>(
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std::bind(&TestProjectionFactor::evaluateError, &factor,
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std::placeholders::_1, std::placeholders::_2,
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std::placeholders::_3, boost::none, boost::none,
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boost::none)),
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pose, body_P_sensor, point);
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CHECK(assert_equal(H2Expected, H2Actual, 1e-5));
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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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