118 lines
3.5 KiB
C++
118 lines
3.5 KiB
C++
/**
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* @file testPose2Constraint.cpp
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* @brief Unit tests for Pose2Factor Class
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* @authors Frank Dellaert, Viorela Ila
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**/
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/*STL/C++*/
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#include <iostream>
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#include <boost/shared_ptr.hpp>
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#include <boost/assign/std/list.hpp>
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using namespace boost::assign;
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#include <CppUnitLite/TestHarness.h>
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#include "NonlinearOptimizer-inl.h"
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#include "NonlinearEquality.h"
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#include "Pose2Factor.h"
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#include "Pose2Graph.h"
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using namespace std;
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using namespace gtsam;
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/* ************************************************************************* */
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TEST( Pose2Factor, linearize )
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{
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// create a factor between unknown poses p1 and p2
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Pose2 measured(2,2,M_PI_2);
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Matrix measurement_covariance = Matrix_(3,3,
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0.25, 0.0, 0.0,
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0.0, 0.25, 0.0,
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0.0, 0.0, 0.01
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);
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Pose2Factor constraint("p1","p2",measured, measurement_covariance);
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// Choose a linearization point
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Pose2 p1(1.1,2,M_PI_2); // robot at (1.1,2) looking towards y (ground truth is at 1,2, see testPose2)
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Pose2 p2(-1,4.1,M_PI); // robot at (-1,4.1) looking at negative (ground truth is at 4.1,2)
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Pose2Config config;
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config.insert("p1",p1);
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config.insert("p2",p2);
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// expected linearization
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// we need the minus signs below as "inverse_square_root"
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// uses SVD and the sign is simply arbitrary (but still a square root!)
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Matrix square_root_inverse_covariance = Matrix_(3,3,
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-2.0, 0.0, 0.0,
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0.0, -2.0, 0.0,
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0.0, 0.0, -10.0
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);
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Matrix expectedH1 = Matrix_(3,3,
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0.0,-1.0,-2.1,
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1.0, 0.0,-2.1,
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0.0, 0.0,-1.0
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);
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Matrix expectedH2 = Matrix_(3,3,
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1.0, 0.0, 0.0,
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0.0, 1.0, 0.0,
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0.0, 0.0, 1.0
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);
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GaussianFactor expected(
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"p1", square_root_inverse_covariance*expectedH1,
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"p2", square_root_inverse_covariance*expectedH2,
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Vector_(3, 0.1, -0.1, 0.0), 1.0);
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// Actual linearization
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boost::shared_ptr<GaussianFactor> actual = constraint.linearize(config);
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CHECK(assert_equal(expected,*actual));
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}
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/* ************************************************************************* */
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bool poseCompare(const std::string& key,
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const gtsam::Pose2Config& feasible,
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const gtsam::Pose2Config& input) {
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return feasible.get(key).equals(input.get(key));
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}
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/* ************************************************************************* */
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TEST(Pose2Factor, optimize) {
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// create a Pose graph with one equality constraint and one measurement
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Pose2Graph fg;
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Pose2Config feasible;
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feasible.insert("p0", Pose2(0,0,0));
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fg.push_back(Pose2Graph::sharedFactor(
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new NonlinearEquality<Pose2Config>("p0", feasible, Pose2().dim(), poseCompare)));
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fg.push_back(Pose2Graph::sharedFactor(
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new Pose2Factor("p0", "p1", Pose2(1,2,M_PI_2), Matrix_(3,3,
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0.5, 0.0, 0.0,
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0.0, 0.5, 0.0,
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0.0, 0.0, 0.5))));
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// Create initial config
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boost::shared_ptr<Pose2Config> initial =
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boost::shared_ptr<Pose2Config>(new Pose2Config());
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initial->insert("p0", Pose2(0,0,0));
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initial->insert("p1", Pose2(0,0,0));
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// Choose an ordering and optimize
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Ordering ordering;
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ordering += "p0","p1";
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NonlinearOptimizer<Pose2Graph, Pose2Config> optimizer(fg, ordering, initial);
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optimizer = optimizer.levenbergMarquardt(1e-15, 1e-15);
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// Check with expected config
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Pose2Config expected;
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expected.insert("p0", Pose2(0,0,0));
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expected.insert("p1", Pose2(1,2,M_PI_2));
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CHECK(assert_equal(expected, *optimizer.config()));
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}
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/* ************************************************************************* */
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int main() {
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TestResult tr;
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return TestRegistry::runAllTests(tr);
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}
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/* ************************************************************************* */
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