86 lines
3.4 KiB
C++
86 lines
3.4 KiB
C++
/*
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* testInvDepthFactorVariant3.cpp
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*
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* Created on: Apr 13, 2012
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* Author: cbeall3
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*/
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#include <CppUnitLite/TestHarness.h>
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#include <gtsam_unstable/slam/InvDepthFactorVariant3.h>
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#include <gtsam/nonlinear/NonlinearEquality.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/geometry/PinholeCamera.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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using namespace std;
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using namespace gtsam;
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/* ************************************************************************* */
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TEST( InvDepthFactorVariant3, optimize) {
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// Create two poses looking in the x-direction
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Pose3 pose1(Rot3::Ypr(-M_PI/2, 0., -M_PI/2), gtsam::Point3(0,0,1.0));
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Pose3 pose2(Rot3::Ypr(-M_PI/2, 0., -M_PI/2), gtsam::Point3(0,0,1.5));
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// Create a landmark 5 meters in front of pose1 (camera center at (0,0,1))
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Point3 landmark(5, 0, 1);
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// Create image observations
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Cal3_S2::shared_ptr K(new Cal3_S2(1500, 1200, 0, 640, 480));
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PinholeCamera<Cal3_S2> camera1(pose1, *K);
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PinholeCamera<Cal3_S2> camera2(pose2, *K);
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Point2 pixel1 = camera1.project(landmark);
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Point2 pixel2 = camera2.project(landmark);
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// Create expected landmark
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Point3 landmark_p1 = pose1.transform_to(landmark);
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// landmark_p1.print("Landmark in Pose1 Frame:\n");
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double theta = atan2(landmark_p1.x(), landmark_p1.z());
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double phi = atan2(landmark_p1.y(), sqrt(landmark_p1.x()*landmark_p1.x()+landmark_p1.z()*landmark_p1.z()));
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double rho = 1./landmark_p1.norm();
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Vector3 expected((Vector(3) << theta, phi, rho).finished());
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// Create a factor graph with two inverse depth factors and two pose priors
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Key poseKey1(1);
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Key poseKey2(2);
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Key landmarkKey(100);
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SharedNoiseModel sigma(noiseModel::Unit::Create(2));
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NonlinearFactor::shared_ptr factor1(new NonlinearEquality<Pose3>(poseKey1, pose1, 100000));
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NonlinearFactor::shared_ptr factor2(new NonlinearEquality<Pose3>(poseKey2, pose2, 100000));
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NonlinearFactor::shared_ptr factor3(new InvDepthFactorVariant3a(poseKey1, landmarkKey, pixel1, K, sigma));
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NonlinearFactor::shared_ptr factor4(new InvDepthFactorVariant3b(poseKey1, poseKey2, landmarkKey, pixel2, K, sigma));
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NonlinearFactorGraph graph;
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graph.push_back(factor1);
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graph.push_back(factor2);
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graph.push_back(factor3);
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graph.push_back(factor4);
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// Create a values with slightly incorrect initial conditions
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Values values;
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values.insert(poseKey1, pose1.retract((Vector(6) << +0.01, -0.02, +0.03, -0.10, +0.20, -0.30).finished()));
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values.insert(poseKey2, pose2.retract((Vector(6) << +0.01, +0.02, -0.03, -0.10, +0.20, +0.30).finished()));
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values.insert(landmarkKey, Vector3(expected + Vector3(+0.02, -0.04, +0.05)));
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// Optimize the graph to recover the actual landmark position
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LevenbergMarquardtParams params;
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Values result = LevenbergMarquardtOptimizer(graph, values, params).optimize();
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Vector3 actual = result.at<Vector3>(landmarkKey);
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// Test that the correct landmark parameters have been recovered
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EXPECT(assert_equal((Vector)expected, actual, 1e-9));
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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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