gtsam/gtsam_unstable/slam/tests/testProjectionFactorPPP.cpp

234 lines
8.4 KiB
C++

/* ----------------------------------------------------------------------------
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
* Atlanta, Georgia 30332-0415
* All Rights Reserved
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
* See LICENSE for the license information
* -------------------------------------------------------------------------- */
/**
* @file testProjectionFactor.cpp
* @brief Unit tests for ProjectionFactorPPP Class
* @author Chris Beall
* @date July 2014
*/
#include <gtsam/base/numericalDerivative.h>
#include <gtsam/base/TestableAssertions.h>
#include <gtsam_unstable/slam/ProjectionFactorPPP.h>
#include <gtsam/inference/Symbol.h>
#include <gtsam/geometry/Cal3DS2.h>
#include <gtsam/geometry/Cal3_S2.h>
#include <gtsam/geometry/Pose3.h>
#include <gtsam/geometry/Point3.h>
#include <gtsam/geometry/Point2.h>
#include <CppUnitLite/TestHarness.h>
using namespace std::placeholders;
using namespace std;
using namespace gtsam;
// make a realistic calibration matrix
static double fov = 60; // degrees
static size_t w=640,h=480;
static Cal3_S2::shared_ptr K(new Cal3_S2(fov,w,h));
// Create a noise model for the pixel error
static SharedNoiseModel model(noiseModel::Unit::Create(2));
// Convenience for named keys
using symbol_shorthand::X;
using symbol_shorthand::L;
using symbol_shorthand::T;
typedef ProjectionFactorPPP<Pose3, Point3> TestProjectionFactor;
/// traits
namespace gtsam {
template<>
struct traits<TestProjectionFactor> : public Testable<TestProjectionFactor> {
};
}
/* ************************************************************************* */
TEST( ProjectionFactorPPP, nonStandard ) {
ProjectionFactorPPP<Pose3, Point3, Cal3DS2> f;
}
/* ************************************************************************* */
TEST( ProjectionFactorPPP, Constructor) {
Key poseKey(X(1));
Key transformKey(T(1));
Key pointKey(L(1));
Point2 measurement(323.0, 240.0);
TestProjectionFactor factor(measurement, model, poseKey, transformKey, pointKey, K);
}
/* ************************************************************************* */
TEST( ProjectionFactorPPP, ConstructorWithTransform) {
Key poseKey(X(1));
Key transformKey(T(1));
Key pointKey(L(1));
Point2 measurement(323.0, 240.0);
TestProjectionFactor factor(measurement, model, poseKey, transformKey, pointKey, K);
}
/* ************************************************************************* */
TEST( ProjectionFactorPPP, Equals ) {
// Create two identical factors and make sure they're equal
Point2 measurement(323.0, 240.0);
TestProjectionFactor factor1(measurement, model, X(1), T(1), L(1), K);
TestProjectionFactor factor2(measurement, model, X(1), T(1), L(1), K);
CHECK(assert_equal(factor1, factor2));
}
/* ************************************************************************* */
TEST( ProjectionFactorPPP, 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), T(1), L(1), K);
TestProjectionFactor factor2(measurement, model, X(1), T(1), L(1), K);
CHECK(assert_equal(factor1, factor2));
}
/* ************************************************************************* */
TEST( ProjectionFactorPPP, Error ) {
// Create the factor with a measurement that is 3 pixels off in x
Key poseKey(X(1));
Key transformKey(T(1));
Key pointKey(L(1));
Point2 measurement(323.0, 240.0);
TestProjectionFactor factor(measurement, model, poseKey, transformKey, 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, Pose3(), point));
// The expected error is (-3.0, 0.0) pixels / UnitCovariance
Vector expectedError = Vector2(-3.0, 0.0);
// Verify we get the expected error
CHECK(assert_equal(expectedError, actualError, 1e-9));
}
/* ************************************************************************* */
TEST( ProjectionFactorPPP, ErrorWithTransform ) {
// Create the factor with a measurement that is 3 pixels off in x
Key poseKey(X(1));
Key transformKey(T(1));
Key pointKey(L(1));
Point2 measurement(323.0, 240.0);
Pose3 transform(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
TestProjectionFactor factor(measurement, model, poseKey,transformKey, pointKey, K);
// 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, transform, point));
// The expected error is (-3.0, 0.0) pixels / UnitCovariance
Vector expectedError = Vector2(-3.0, 0.0);
// Verify we get the expected error
CHECK(assert_equal(expectedError, actualError, 1e-9));
}
/* ************************************************************************* */
TEST( ProjectionFactorPPP, Jacobian ) {
// Create the factor with a measurement that is 3 pixels off in x
Key poseKey(X(1));
Key transformKey(T(1));
Key pointKey(L(1));
Point2 measurement(323.0, 240.0);
TestProjectionFactor factor(measurement, model, poseKey, transformKey, 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, H3Actual;
factor.evaluateError(pose, Pose3(), point, H1Actual, H2Actual, H3Actual);
// The expected Jacobians
Matrix H1Expected = (Matrix(2, 6) << 0., -554.256, 0., -92.376, 0., 0., 554.256, 0., 0., 0., -92.376, 0.).finished();
Matrix H3Expected = (Matrix(2, 3) << 92.376, 0., 0., 0., 92.376, 0.).finished();
// Verify the Jacobians are correct
CHECK(assert_equal(H1Expected, H1Actual, 1e-3));
CHECK(assert_equal(H3Expected, H3Actual, 1e-3));
// Verify H2 with numerical derivative
Matrix H2Expected = numericalDerivative32<Vector, Pose3, Pose3, Point3>(
std::function<Vector(const Pose3&, const Pose3&, const Point3&)>(
std::bind(&TestProjectionFactor::evaluateError, &factor,
std::placeholders::_1, std::placeholders::_2,
std::placeholders::_3, boost::none, boost::none,
boost::none)),
pose, Pose3(), point);
CHECK(assert_equal(H2Expected, H2Actual, 1e-5));
}
/* ************************************************************************* */
TEST( ProjectionFactorPPP, JacobianWithTransform ) {
// Create the factor with a measurement that is 3 pixels off in x
Key poseKey(X(1));
Key transformKey(T(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, transformKey, pointKey, K);
// 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, H3Actual;
factor.evaluateError(pose, body_P_sensor, point, H1Actual, H2Actual, H3Actual);
// 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).finished();
Matrix H3Expected = (Matrix(2, 3) << 0., -92.376, 0., 0., 0., -92.376).finished();
// Verify the Jacobians are correct
CHECK(assert_equal(H1Expected, H1Actual, 1e-3));
CHECK(assert_equal(H3Expected, H3Actual, 1e-3));
// Verify H2 with numerical derivative
Matrix H2Expected = numericalDerivative32<Vector, Pose3, Pose3, Point3>(
std::function<Vector(const Pose3&, const Pose3&, const Point3&)>(
std::bind(&TestProjectionFactor::evaluateError, &factor,
std::placeholders::_1, std::placeholders::_2,
std::placeholders::_3, boost::none, boost::none,
boost::none)),
pose, body_P_sensor, point);
CHECK(assert_equal(H2Expected, H2Actual, 1e-5));
}
/* ************************************************************************* */
int main() { TestResult tr; return TestRegistry::runAllTests(tr); }
/* ************************************************************************* */