233 lines
8.3 KiB
C++
233 lines
8.3 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 ProjectionFactor Class
|
|
* @author Frank Dellaert
|
|
* @date Nov 2009
|
|
*/
|
|
|
|
#include <gtsam/slam/BetweenFactor.h>
|
|
#include <gtsam/slam/ProjectionFactor.h>
|
|
#include <gtsam_unstable/slam/MultiProjectionFactor.h>
|
|
#include <gtsam/nonlinear/ISAM2.h>
|
|
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
|
|
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
|
|
#include <gtsam/nonlinear/LinearContainerFactor.h>
|
|
#include <gtsam/inference/Ordering.h>
|
|
#include <gtsam/nonlinear/Values.h>
|
|
#include <gtsam/inference/Symbol.h>
|
|
#include <gtsam/inference/Key.h>
|
|
#include <gtsam/inference/JunctionTree.h>
|
|
#include <gtsam/geometry/Pose3.h>
|
|
#include <gtsam/geometry/Point3.h>
|
|
#include <gtsam/geometry/Point2.h>
|
|
#include <gtsam/geometry/Cal3DS2.h>
|
|
#include <gtsam/geometry/Cal3_S2.h>
|
|
#include <CppUnitLite/TestHarness.h>
|
|
|
|
|
|
using namespace std;
|
|
using namespace gtsam;
|
|
|
|
// make a realistic calibration matrix
|
|
static double fov = 60; // degrees
|
|
static int 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;
|
|
|
|
//typedef GenericProjectionFactor<Pose3, Point3> TestProjectionFactor;
|
|
|
|
|
|
///* ************************************************************************* */
|
|
TEST( MultiProjectionFactor, create ){
|
|
Values theta;
|
|
NonlinearFactorGraph graph;
|
|
|
|
Symbol x1('X', 1);
|
|
Symbol x2('X', 2);
|
|
Symbol x3('X', 3);
|
|
|
|
Symbol l1('l', 1);
|
|
Vector n_measPixel(6); // Pixel measurements from 3 cameras observing landmark 1
|
|
n_measPixel << 10, 10, 10, 10, 10, 10;
|
|
const SharedDiagonal noiseProjection = noiseModel::Isotropic::Sigma(2, 1);
|
|
|
|
KeySet views;
|
|
views.insert(x1);
|
|
views.insert(x2);
|
|
views.insert(x3);
|
|
|
|
MultiProjectionFactor<Pose3, Point3> mpFactor(n_measPixel, noiseProjection, views, l1, K);
|
|
graph += mpFactor;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
///* ************************************************************************* */
|
|
//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 = Vector2(-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 = Vector2(-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.).finished();
|
|
// Matrix H2Expected = (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(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).finished();
|
|
// Matrix H2Expected = (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(H2Expected, H2Actual, 1e-3));
|
|
//}
|
|
|
|
/* ************************************************************************* */
|
|
int main() { TestResult tr; return TestRegistry::runAllTests(tr); }
|
|
/* ************************************************************************* */
|
|
|