gtsam/gtsam/slam/tests/testStereoFactor.cpp

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