/* ---------------------------------------------------------------------------- * 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 testSimilarity3.cpp * @brief Unit tests for Similarity3 class * @author Paul Drews * @author Zhaoyang Lv */ #include #include #include #include #include #include #include #include #include #include #include #include #include #include using namespace gtsam; using namespace std; using symbol_shorthand::X; GTSAM_CONCEPT_TESTABLE_INST(Similarity3) static const Point3 P(0.2, 0.7, -2); static const Rot3 R = Rot3::Rodrigues(0.3, 0, 0); static const double s = 4; static const Similarity3 id; static const Similarity3 T1(R, Point3(3.5, -8.2, 4.2), 1); static const Similarity3 T2(Rot3::Rodrigues(0.3, 0.2, 0.1), Point3(3.5, -8.2, 4.2), 1); static const Similarity3 T3(Rot3::Rodrigues(-90, 0, 0), Point3(1, 2, 3), 1); static const Similarity3 T4(R, P, s); static const Similarity3 T5(R, P, 10); static const Similarity3 T6(Rot3(), Point3(1, 1, 0), 2); // Simpler transform //****************************************************************************** TEST(Similarity3, Concepts) { BOOST_CONCEPT_ASSERT((IsGroup)); BOOST_CONCEPT_ASSERT((IsManifold)); BOOST_CONCEPT_ASSERT((IsLieGroup)); } //****************************************************************************** TEST(Similarity3, Constructors) { Similarity3 sim3_Construct1; Similarity3 sim3_Construct2(s); Similarity3 sim3_Construct3(R, P, s); Similarity3 sim4_Construct4(R.matrix(), P, s); } //****************************************************************************** TEST(Similarity3, Getters) { Similarity3 sim3_default; EXPECT(assert_equal(Rot3(), sim3_default.rotation())); EXPECT(assert_equal(Point3(0,0,0), sim3_default.translation())); EXPECT_DOUBLES_EQUAL(1.0, sim3_default.scale(), 1e-9); Similarity3 sim3(Rot3::Ypr(1, 2, 3), Point3(4, 5, 6), 7); EXPECT(assert_equal(Rot3::Ypr(1, 2, 3), sim3.rotation())); EXPECT(assert_equal(Point3(4, 5, 6), sim3.translation())); EXPECT_DOUBLES_EQUAL(7.0, sim3.scale(), 1e-9); } //****************************************************************************** TEST(Similarity3, AdjointMap) { const Matrix4 T = T2.matrix(); // Check Ad with actual definition Vector7 delta; delta << 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7; Matrix4 W = Similarity3::wedge(delta); Matrix4 TW = Similarity3::wedge(T2.AdjointMap() * delta); EXPECT(assert_equal(TW, Matrix4(T * W * T.inverse()), 1e-9)); } //****************************************************************************** TEST(Similarity3, inverse) { Similarity3 sim3(Rot3::Ypr(1, 2, 3).inverse(), Point3(4, 5, 6), 7); Matrix3 Re; // some values from matlab Re << -0.2248, 0.9024, -0.3676, -0.3502, -0.4269, -0.8337, -0.9093, -0.0587, 0.4120; Vector3 te(-9.8472, 59.7640, 10.2125); Similarity3 expected(Re, te, 1.0 / 7.0); EXPECT(assert_equal(expected, sim3.inverse(), 1e-4)); EXPECT(assert_equal(sim3, sim3.inverse().inverse(), 1e-8)); // test lie group inverse Matrix H1, H2; EXPECT(assert_equal(expected, sim3.inverse(H1), 1e-4)); EXPECT(assert_equal(sim3, sim3.inverse().inverse(H2), 1e-8)); } //****************************************************************************** TEST(Similarity3, Multiplication) { Similarity3 test1(Rot3::Ypr(1, 2, 3).inverse(), Point3(4, 5, 6), 7); Similarity3 test2(Rot3::Ypr(1, 2, 3).inverse(), Point3(8, 9, 10), 11); Matrix3 re; re << 0.0688, 0.9863, -0.1496, -0.5665, -0.0848, -0.8197, -0.8211, 0.1412, 0.5530; Vector3 te(-13.6797, 3.2441, -5.7794); Similarity3 expected(re, te, 77); EXPECT(assert_equal(expected, test1 * test2, 1e-2)); } //****************************************************************************** TEST(Similarity3, Manifold) { EXPECT_LONGS_EQUAL(7, Similarity3::Dim()); Vector z = Vector7::Zero(); Similarity3 sim; EXPECT(sim.retract(z) == sim); Vector7 v = Vector7::Zero(); v(6) = 2; Similarity3 sim2; EXPECT(sim2.retract(z) == sim2); EXPECT(assert_equal(z, sim2.localCoordinates(sim))); Similarity3 sim3 = Similarity3(Rot3(), Point3(1, 2, 3), 1); Vector v3(7); v3 << 0, 0, 0, 1, 2, 3, 0; EXPECT(assert_equal(v3, sim2.localCoordinates(sim3))); Similarity3 other = Similarity3(Rot3::Ypr(0.1, 0.2, 0.3), Point3(4, 5, 6), 1); Vector vlocal = sim.localCoordinates(other); EXPECT(assert_equal(sim.retract(vlocal), other, 1e-2)); Similarity3 other2 = Similarity3(Rot3::Ypr(0.3, 0, 0), Point3(4, 5, 6), 1); Rot3 R = Rot3::Rodrigues(0.3, 0, 0); Vector vlocal2 = sim.localCoordinates(other2); EXPECT(assert_equal(sim.retract(vlocal2), other2, 1e-2)); // TODO add unit tests for retract and localCoordinates } //****************************************************************************** TEST( Similarity3, retract_first_order) { Similarity3 id; Vector v = Z_7x1; v(0) = 0.3; EXPECT(assert_equal(Similarity3(R, Point3(0,0,0), 1), id.retract(v), 1e-2)); // v(3) = 0.2; // v(4) = 0.7; // v(5) = -2; // EXPECT(assert_equal(Similarity3(R, P, 1), id.retract(v), 1e-2)); } //****************************************************************************** TEST(Similarity3, localCoordinates_first_order) { Vector7 d12 = Vector7::Constant(0.1); d12(6) = 1.0; Similarity3 t1 = T1, t2 = t1.retract(d12); EXPECT(assert_equal(d12, t1.localCoordinates(t2))); } //****************************************************************************** TEST(Similarity3, manifold_first_order) { Similarity3 t1 = T1; Similarity3 t2 = T3; Similarity3 origin; Vector d12 = t1.localCoordinates(t2); EXPECT(assert_equal(t2, t1.retract(d12))); Vector d21 = t2.localCoordinates(t1); EXPECT(assert_equal(t1, t2.retract(d21))); } //****************************************************************************** // Return as a 4*4 Matrix TEST(Similarity3, Matrix) { Matrix4 expected; expected << 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0.5; Matrix4 actual = T6.matrix(); EXPECT(assert_equal(expected, actual)); } //***************************************************************************** // Exponential and log maps TEST(Similarity3, ExpLogMap) { Vector7 delta; delta << 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7; Vector7 actual = Similarity3::Logmap(Similarity3::Expmap(delta)); EXPECT(assert_equal(delta, actual)); Vector7 zeros; zeros << 0, 0, 0, 0, 0, 0, 0; Vector7 logIdentity = Similarity3::Logmap(Similarity3::identity()); EXPECT(assert_equal(zeros, logIdentity)); Similarity3 expZero = Similarity3::Expmap(zeros); Similarity3 ident = Similarity3::identity(); EXPECT(assert_equal(expZero, ident)); // Compare to matrix exponential, using expm in Lie.h EXPECT( assert_equal(expm(delta), Similarity3::Expmap(delta), 1e-3)); } //****************************************************************************** // Group action on Point3 (with simpler transform) TEST(Similarity3, GroupAction) { EXPECT(assert_equal(Point3(2, 2, 0), T6 * Point3(0, 0, 0))); EXPECT(assert_equal(Point3(4, 2, 0), T6 * Point3(1, 0, 0))); // Test group action on R^4 via matrix representation Vector4 qh; qh << 1, 0, 0, 1; Vector4 ph; ph << 2, 1, 0, 0.5; // equivalent to Point3(4, 2, 0) EXPECT(assert_equal((Vector )ph, T6.matrix() * qh)); // Test some more... Point3 pa = Point3(1, 0, 0); Similarity3 Ta(Rot3(), Point3(1, 2, 3), 1.0); Similarity3 Tb(Rot3(), Point3(1, 2, 3), 2.0); EXPECT(assert_equal(Point3(2, 2, 3), Ta.transformFrom(pa))); EXPECT(assert_equal(Point3(4, 4, 6), Tb.transformFrom(pa))); Similarity3 Tc(Rot3::Rz(M_PI / 2.0), Point3(1, 2, 3), 1.0); Similarity3 Td(Rot3::Rz(M_PI / 2.0), Point3(1, 2, 3), 2.0); EXPECT(assert_equal(Point3(1, 3, 3), Tc.transformFrom(pa))); EXPECT(assert_equal(Point3(2, 6, 6), Td.transformFrom(pa))); // Test derivative boost::function f = boost::bind( &Similarity3::transformFrom, _1, _2, boost::none, boost::none); Point3 q(1, 2, 3); for (const auto T : { T1, T2, T3, T4, T5, T6 }) { Point3 q(1, 0, 0); Matrix H1 = numericalDerivative21(f, T, q); Matrix H2 = numericalDerivative22(f, T, q); Matrix actualH1, actualH2; T.transformFrom(q, actualH1, actualH2); EXPECT(assert_equal(H1, actualH1)); EXPECT(assert_equal(H2, actualH2)); } } //****************************************************************************** // Test very simple prior optimization example TEST(Similarity3, Optimization) { // Create a PriorFactor with a Sim3 prior Similarity3 prior = Similarity3(Rot3::Ypr(0.1, 0.2, 0.3), Point3(1, 2, 3), 4); noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(7, 1); Symbol key('x', 1); // Create graph NonlinearFactorGraph graph; graph.addPrior(key, prior, model); // Create initial estimate with identity transform Values initial; initial.insert(key, Similarity3()); // Optimize Values result; LevenbergMarquardtParams params; params.setVerbosityLM("TRYCONFIG"); result = LevenbergMarquardtOptimizer(graph, initial).optimize(); // After optimization, result should be prior EXPECT(assert_equal(prior, result.at(key), 1e-4)); } //****************************************************************************** // Test optimization with both Prior and BetweenFactors TEST(Similarity3, Optimization2) { Similarity3 prior = Similarity3(); Similarity3 m1 = Similarity3(Rot3::Ypr(M_PI / 4.0, 0, 0), Point3(2.0, 0, 0), 1.0); Similarity3 m2 = Similarity3(Rot3::Ypr(M_PI / 2.0, 0, 0), Point3(sqrt(8) * 0.9, 0, 0), 1.0); Similarity3 m3 = Similarity3(Rot3::Ypr(3 * M_PI / 4.0, 0, 0), Point3(sqrt(32) * 0.8, 0, 0), 1.0); Similarity3 m4 = Similarity3(Rot3::Ypr(M_PI / 2.0, 0, 0), Point3(6 * 0.7, 0, 0), 1.0); Similarity3 loop = Similarity3(1.42); //prior.print("Goal Transform"); noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(7, 0.01); SharedDiagonal betweenNoise = noiseModel::Diagonal::Sigmas( (Vector(7) << 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 10).finished()); SharedDiagonal betweenNoise2 = noiseModel::Diagonal::Sigmas( (Vector(7) << 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 1.0).finished()); BetweenFactor b1(X(1), X(2), m1, betweenNoise); BetweenFactor b2(X(2), X(3), m2, betweenNoise); BetweenFactor b3(X(3), X(4), m3, betweenNoise); BetweenFactor b4(X(4), X(5), m4, betweenNoise); BetweenFactor lc(X(5), X(1), loop, betweenNoise2); // Create graph NonlinearFactorGraph graph; graph.addPrior(X(1), prior, model); // Prior ! graph.push_back(b1); graph.push_back(b2); graph.push_back(b3); graph.push_back(b4); graph.push_back(lc); //graph.print("Full Graph\n"); Values initial; initial.insert(X(1), Similarity3()); initial.insert(X(2), Similarity3(Rot3::Ypr(M_PI / 2.0, 0, 0), Point3(1, 0, 0), 1.1)); initial.insert(X(3), Similarity3(Rot3::Ypr(2.0 * M_PI / 2.0, 0, 0), Point3(0.9, 1.1, 0), 1.2)); initial.insert(X(4), Similarity3(Rot3::Ypr(3.0 * M_PI / 2.0, 0, 0), Point3(0, 1, 0), 1.3)); initial.insert(X(5), Similarity3(Rot3::Ypr(4.0 * M_PI / 2.0, 0, 0), Point3(0, 0, 0), 1.0)); //initial.print("Initial Estimate\n"); Values result; result = LevenbergMarquardtOptimizer(graph, initial).optimize(); //result.print("Optimized Estimate\n"); Pose3 p1, p2, p3, p4, p5; p1 = Pose3(result.at(X(1))); p2 = Pose3(result.at(X(2))); p3 = Pose3(result.at(X(3))); p4 = Pose3(result.at(X(4))); p5 = Pose3(result.at(X(5))); //p1.print("Pose1"); //p2.print("Pose2"); //p3.print("Pose3"); //p4.print("Pose4"); //p5.print("Pose5"); Similarity3 expected(0.7); EXPECT(assert_equal(expected, result.at(X(5)), 0.4)); } //****************************************************************************** // Align points (p,q) assuming that p = T*q + noise TEST(Similarity3, AlignScaledPointClouds) { // Create ground truth Point3 q1(0, 0, 0), q2(1, 0, 0), q3(0, 1, 0); // Create transformed cloud (noiseless) // Point3 p1 = T4 * q1, p2 = T4 * q2, p3 = T4 * q3; // Create an unknown expression Expression unknownT(0); // use key 0 // Create constant expressions for the ground truth points Expression q1_(q1), q2_(q2), q3_(q3); // Create prediction expressions Expression predict1(unknownT, &Similarity3::transformFrom, q1_); Expression predict2(unknownT, &Similarity3::transformFrom, q2_); Expression predict3(unknownT, &Similarity3::transformFrom, q3_); //// Create Expression factor graph // ExpressionFactorGraph graph; // graph.addExpressionFactor(predict1, p1, R); // |T*q1 - p1| // graph.addExpressionFactor(predict2, p2, R); // |T*q2 - p2| // graph.addExpressionFactor(predict3, p3, R); // |T*q3 - p3| } //****************************************************************************** TEST(Similarity3 , Invariants) { Similarity3 id; EXPECT(check_group_invariants(id, id)); EXPECT(check_group_invariants(id, T3)); EXPECT(check_group_invariants(T2, id)); EXPECT(check_group_invariants(T2, T3)); EXPECT(check_manifold_invariants(id, id)); EXPECT(check_manifold_invariants(id, T3)); EXPECT(check_manifold_invariants(T2, id)); EXPECT(check_manifold_invariants(T2, T3)); } //****************************************************************************** TEST(Similarity3 , LieGroupDerivatives) { Similarity3 id; CHECK_LIE_GROUP_DERIVATIVES(id, id); CHECK_LIE_GROUP_DERIVATIVES(id, T2); CHECK_LIE_GROUP_DERIVATIVES(T2, id); CHECK_LIE_GROUP_DERIVATIVES(T2, T3); } //****************************************************************************** int main() { TestResult tr; return TestRegistry::runAllTests(tr); } //******************************************************************************