223 lines
6.9 KiB
C++
223 lines
6.9 KiB
C++
/**
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* @file testPose2Graph.cpp
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* @authors Frank Dellaert, Viorela Ila
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**/
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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;
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using namespace boost::assign;
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#include <CppUnitLite/TestHarness.h>
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#define GTSAM_MAGIC_KEY
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#include "NonlinearOptimizer-inl.h"
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#include "FactorGraph-inl.h"
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#include "Ordering.h"
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#include "pose2SLAM.h"
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#include "Pose2SLAMOptimizer.h"
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using namespace std;
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using namespace gtsam;
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// common measurement covariance
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static double sx=0.5, sy=0.5,st=0.1;
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static noiseModel::Gaussian::shared_ptr covariance(
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noiseModel::Gaussian::Covariance(Matrix_(3, 3,
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sx*sx, 0.0, 0.0,
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0.0, sy*sy, 0.0,
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0.0, 0.0, st*st
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))), I3(noiseModel::Unit::Create(3));
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/* ************************************************************************* */
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TEST( Pose2Graph, constructor )
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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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Pose2Factor constraint(1,2,measured, covariance);
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Pose2Graph graph;
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graph.addConstraint(1,2,measured, covariance);
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// get the size of the graph
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size_t actual = graph.size();
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// verify
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size_t expected = 1;
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CHECK(actual == expected);
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}
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/* ************************************************************************* */
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TEST( Pose2Graph, linearization )
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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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Pose2Factor constraint(1,2,measured, covariance);
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Pose2Graph graph;
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graph.addConstraint(1,2,measured, 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) looking at negative (ground truth is at 4.1,2)
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Pose2Config config;
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config.insert(1,p1);
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config.insert(2,p2);
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// Linearize
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GaussianFactorGraph lfg_linearized = graph.linearize(config);
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//lfg_linearized.print("lfg_actual");
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// the expected linear factor
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GaussianFactorGraph lfg_expected;
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Matrix A1 = Matrix_(3,3,
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0.0,-2.0, -4.2,
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2.0, 0.0, -4.2,
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0.0, 0.0,-10.0);
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Matrix A2 = 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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double sigma = 1;
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Vector b = Vector_(3,-0.1/sx,0.1/sy,0.0);
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SharedDiagonal probModel1 = noiseModel::Unit::Create(3);
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lfg_expected.add("x1", A1, "x2", A2, b, probModel1);
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CHECK(assert_equal(lfg_expected, lfg_linearized));
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}
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/* ************************************************************************* */
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TEST(Pose2Graph, optimize) {
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// create a Pose graph with one equality constraint and one measurement
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shared_ptr<Pose2Graph> fg(new Pose2Graph);
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fg->addHardConstraint(0, Pose2(0,0,0));
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fg->addConstraint(0, 1, Pose2(1,2,M_PI_2), covariance);
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// Create initial config
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boost::shared_ptr<Pose2Config> initial(new Pose2Config());
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initial->insert(0, Pose2(0,0,0));
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initial->insert(1, Pose2(0,0,0));
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// Choose an ordering and optimize
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shared_ptr<Ordering> ordering(new Ordering);
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*ordering += "x0","x1";
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typedef NonlinearOptimizer<Pose2Graph, Pose2Config> Optimizer;
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Optimizer::shared_solver solver(new Optimizer::solver(ordering));
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Optimizer optimizer0(fg, initial, solver);
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Optimizer::verbosityLevel verbosity = Optimizer::SILENT;
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//Optimizer::verbosityLevel verbosity = Optimizer::ERROR;
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Optimizer optimizer = optimizer0.levenbergMarquardt(1e-15, 1e-15, verbosity);
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// Check with expected config
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Pose2Config expected;
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expected.insert(0, Pose2(0,0,0));
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expected.insert(1, 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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// test optimization with 6 poses arranged in a hexagon and a loop closure
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TEST(Pose2Graph, optimizeCircle) {
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// Create a hexagon of poses
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Pose2Config hexagon = pose2SLAM::circle(6,1.0);
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Pose2 p0 = hexagon[0], p1 = hexagon[1];
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// create a Pose graph with one equality constraint and one measurement
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shared_ptr<Pose2Graph> fg(new Pose2Graph);
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fg->addHardConstraint(0, p0);
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Pose2 delta = between(p0,p1);
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fg->addConstraint(0, 1, delta, covariance);
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fg->addConstraint(1,2, delta, covariance);
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fg->addConstraint(2,3, delta, covariance);
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fg->addConstraint(3,4, delta, covariance);
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fg->addConstraint(4,5, delta, covariance);
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fg->addConstraint(5, 0, delta, covariance);
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// Create initial config
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boost::shared_ptr<Pose2Config> initial(new Pose2Config());
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initial->insert(0, p0);
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initial->insert(1, expmap(hexagon[1],Vector_(3,-0.1, 0.1,-0.1)));
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initial->insert(2, expmap(hexagon[2],Vector_(3, 0.1,-0.1, 0.1)));
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initial->insert(3, expmap(hexagon[3],Vector_(3,-0.1, 0.1,-0.1)));
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initial->insert(4, expmap(hexagon[4],Vector_(3, 0.1,-0.1, 0.1)));
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initial->insert(5, expmap(hexagon[5],Vector_(3,-0.1, 0.1,-0.1)));
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// Choose an ordering
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shared_ptr<Ordering> ordering(new Ordering);
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*ordering += "x0","x1","x2","x3","x4","x5";
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// optimize
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pose2SLAM::Optimizer::shared_solver solver(new pose2SLAM::Optimizer::solver(ordering));
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pose2SLAM::Optimizer optimizer0(fg, initial, solver);
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pose2SLAM::Optimizer::verbosityLevel verbosity = pose2SLAM::Optimizer::SILENT;
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pose2SLAM::Optimizer optimizer = optimizer0.levenbergMarquardt(1e-15, 1e-15, verbosity);
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Pose2Config actual = *optimizer.config();
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// Check with ground truth
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CHECK(assert_equal(hexagon, actual));
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// Check loop closure
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CHECK(assert_equal(delta,between(actual[5],actual[0])));
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// Try PCG class
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// Pose2SLAMOptimizer myOptimizer("3");
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// Matrix Ab1 = myOptimizer.Ab1();
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// CHECK(assert_equal(Matrix_(1,1,1.0),Ab1));
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//
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// Matrix Ab2 = myOptimizer.Ab2();
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// CHECK(assert_equal(Matrix_(1,1,1.0),Ab2));
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// Here, call matlab to
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// A=[A1;A2], b=[b1;b2]
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// R=qr(A1)
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// call pcg on A,b, with preconditioner R -> get x
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// Vector x;
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// myOptimizer.update(x);
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// Check with ground truth
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// CHECK(assert_equal(hexagon, *myOptimizer.theta()));
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}
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/* ************************************************************************* */
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TEST(Pose2Graph, findMinimumSpanningTree) {
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Pose2Graph G, T, C;
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G.addConstraint(1, 2, Pose2(0.,0.,0.), I3);
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G.addConstraint(1, 3, Pose2(0.,0.,0.), I3);
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G.addConstraint(2, 3, Pose2(0.,0.,0.), I3);
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PredecessorMap<pose2SLAM::Key> tree =
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G.findMinimumSpanningTree<pose2SLAM::Key, Pose2Factor>();
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CHECK(tree[1] == 1);
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CHECK(tree[2] == 1);
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CHECK(tree[3] == 1);
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}
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/* ************************************************************************* */
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TEST(Pose2Graph, split) {
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Pose2Graph G, T, C;
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G.addConstraint(1, 2, Pose2(0.,0.,0.), I3);
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G.addConstraint(1, 3, Pose2(0.,0.,0.), I3);
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G.addConstraint(2, 3, Pose2(0.,0.,0.), I3);
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PredecessorMap<pose2SLAM::Key> tree;
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tree.insert(1,2);
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tree.insert(2,2);
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tree.insert(3,2);
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G.split<pose2SLAM::Key, Pose2Factor>(tree, T, C);
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LONGS_EQUAL(2, T.size());
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LONGS_EQUAL(1, C.size());
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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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