Merge pull request #325 from borglab/feature/alternate_hatvee_signs
Alternate signs on Hat/Vee and update testsrelease/4.3a0
Akshay Krishnan
GitHub
commit
8ce40a3584
8
gtsam.h
8
gtsam.h
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@ -2294,6 +2294,8 @@ virtual class NonlinearOptimizerParams {
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bool checkConvergence(double relativeErrorTreshold,
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double absoluteErrorTreshold, double errorThreshold,
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double currentError, double newError);
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bool checkConvergence(const gtsam::NonlinearOptimizerParams& params,
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double currentError, double newError);
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#include <gtsam/nonlinear/GaussNewtonOptimizer.h>
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virtual class GaussNewtonParams : gtsam::NonlinearOptimizerParams {
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@ -2529,7 +2531,7 @@ class NonlinearISAM {
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#include <gtsam/geometry/StereoPoint2.h>
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#include <gtsam/nonlinear/PriorFactor.h>
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template<T = {Vector, gtsam::Point2, gtsam::StereoPoint2, gtsam::Point3, gtsam::Rot2, gtsam::SO3, gtsam::SO4, gtsam::Rot3, gtsam::Pose2, gtsam::Pose3, gtsam::Cal3_S2,gtsam::CalibratedCamera, gtsam::SimpleCamera, gtsam::PinholeCameraCal3_S2, gtsam::imuBias::ConstantBias}>
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template<T = {Vector, gtsam::Point2, gtsam::StereoPoint2, gtsam::Point3, gtsam::Rot2, gtsam::SO3, gtsam::SO4, gtsam::SOn, gtsam::Rot3, gtsam::Pose2, gtsam::Pose3, gtsam::Cal3_S2,gtsam::CalibratedCamera, gtsam::SimpleCamera, gtsam::PinholeCameraCal3_S2, gtsam::imuBias::ConstantBias}>
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virtual class PriorFactor : gtsam::NoiseModelFactor {
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PriorFactor(size_t key, const T& prior, const gtsam::noiseModel::Base* noiseModel);
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T prior() const;
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@ -2552,7 +2554,7 @@ virtual class BetweenFactor : gtsam::NoiseModelFactor {
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#include <gtsam/nonlinear/NonlinearEquality.h>
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template<T = {gtsam::Point2, gtsam::StereoPoint2, gtsam::Point3, gtsam::Rot2, gtsam::SO3, gtsam::SO4, gtsam::Rot3, gtsam::Pose2, gtsam::Pose3, gtsam::Cal3_S2, gtsam::CalibratedCamera, gtsam::SimpleCamera, gtsam::PinholeCameraCal3_S2, gtsam::imuBias::ConstantBias}>
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template<T = {gtsam::Point2, gtsam::StereoPoint2, gtsam::Point3, gtsam::Rot2, gtsam::SO3, gtsam::SO4, gtsam::SOn, gtsam::Rot3, gtsam::Pose2, gtsam::Pose3, gtsam::Cal3_S2, gtsam::CalibratedCamera, gtsam::SimpleCamera, gtsam::PinholeCameraCal3_S2, gtsam::imuBias::ConstantBias}>
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virtual class NonlinearEquality : gtsam::NoiseModelFactor {
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// Constructor - forces exact evaluation
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NonlinearEquality(size_t j, const T& feasible);
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@ -2793,8 +2795,10 @@ void save2D(const gtsam::NonlinearFactorGraph& graph,
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// std::vector<gtsam::BetweenFactor<Pose3>::shared_ptr>
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class BetweenFactorPose3s
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{
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BetweenFactorPose3s();
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size_t size() const;
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gtsam::BetweenFactorPose3* at(size_t i) const;
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void push_back(const gtsam::BetweenFactorPose3* factor);
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};
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#include <gtsam/slam/InitializePose3.h>
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@ -170,7 +170,7 @@ namespace internal {
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/// Assumes existence of: identity, dimension, localCoordinates, retract,
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/// and additionally Logmap, Expmap, compose, between, and inverse
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template<class Class>
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struct LieGroupTraits {
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struct LieGroupTraits: GetDimensionImpl<Class, Class::dimension> {
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typedef lie_group_tag structure_category;
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/// @name Group
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@ -186,8 +186,6 @@ struct LieGroupTraits {
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typedef Eigen::Matrix<double, dimension, 1> TangentVector;
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typedef OptionalJacobian<dimension, dimension> ChartJacobian;
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static int GetDimension(const Class&) {return dimension;}
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static TangentVector Local(const Class& origin, const Class& other,
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ChartJacobian Horigin = boost::none, ChartJacobian Hother = boost::none) {
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return origin.localCoordinates(other, Horigin, Hother);
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@ -72,7 +72,7 @@ struct HasManifoldPrereqs {
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/// Extra manifold traits for fixed-dimension types
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template<class Class, int N>
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struct ManifoldImpl {
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struct GetDimensionImpl {
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// Compile-time dimensionality
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static int GetDimension(const Class&) {
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return N;
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@ -81,7 +81,7 @@ struct ManifoldImpl {
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/// Extra manifold traits for variable-dimension types
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template<class Class>
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struct ManifoldImpl<Class, Eigen::Dynamic> {
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struct GetDimensionImpl<Class, Eigen::Dynamic> {
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// Run-time dimensionality
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static int GetDimension(const Class& m) {
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return m.dim();
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@ -92,7 +92,7 @@ struct ManifoldImpl<Class, Eigen::Dynamic> {
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/// To use this for your class type, define:
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/// template<> struct traits<Class> : public internal::ManifoldTraits<Class> { };
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template<class Class>
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struct ManifoldTraits: ManifoldImpl<Class, Class::dimension> {
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struct ManifoldTraits: GetDimensionImpl<Class, Class::dimension> {
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// Check that Class has the necessary machinery
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BOOST_CONCEPT_ASSERT((HasManifoldPrereqs<Class>));
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@ -261,13 +261,13 @@ Vector3 SO3::Logmap(const SO3& Q, ChartJacobian H) {
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// when trace == -1, i.e., when theta = +-pi, +-3pi, +-5pi, etc.
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// we do something special
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if (std::abs(tr + 1.0) < 1e-10) {
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if (std::abs(R33 + 1.0) > 1e-10)
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if (tr + 1.0 < 1e-10) {
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if (std::abs(R33 + 1.0) > 1e-5)
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omega = (M_PI / sqrt(2.0 + 2.0 * R33)) * Vector3(R13, R23, 1.0 + R33);
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else if (std::abs(R22 + 1.0) > 1e-10)
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else if (std::abs(R22 + 1.0) > 1e-5)
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omega = (M_PI / sqrt(2.0 + 2.0 * R22)) * Vector3(R12, 1.0 + R22, R32);
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else
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// if(std::abs(R.r1_.x()+1.0) > 1e-10) This is implicit
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// if(std::abs(R.r1_.x()+1.0) > 1e-5) This is implicit
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omega = (M_PI / sqrt(2.0 + 2.0 * R11)) * Vector3(1.0 + R11, R21, R31);
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} else {
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double magnitude;
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@ -33,9 +33,10 @@ using namespace std;
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namespace gtsam {
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// TODO(frank): is this better than SOn::Random?
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// /* *************************************************************************
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// */ static Vector3 randomOmega(boost::mt19937 &rng) {
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// static boost::uniform_real<double> randomAngle(-M_PI, M_PI);
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// static std::uniform_real_distribution<double> randomAngle(-M_PI, M_PI);
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// return Unit3::Random(rng).unitVector() * randomAngle(rng);
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// }
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@ -58,9 +59,9 @@ Matrix4 SO4::Hat(const Vector6& xi) {
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Y(0, 1) = -xi(5);
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Y(0, 2) = +xi(4);
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Y(1, 2) = -xi(3);
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Y(0, 3) = -xi(2);
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Y(1, 3) = +xi(1);
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Y(2, 3) = -xi(0);
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Y(0, 3) = +xi(2);
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Y(1, 3) = -xi(1);
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Y(2, 3) = +xi(0);
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return Y - Y.transpose();
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}
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@ -72,9 +73,9 @@ Vector6 SO4::Vee(const Matrix4& X) {
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xi(5) = -X(0, 1);
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xi(4) = +X(0, 2);
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xi(3) = -X(1, 2);
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xi(2) = -X(0, 3);
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xi(1) = +X(1, 3);
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xi(0) = -X(2, 3);
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xi(2) = +X(0, 3);
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xi(1) = -X(1, 3);
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xi(0) = +X(2, 3);
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return xi;
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}
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@ -208,9 +209,9 @@ GTSAM_EXPORT Matrix3 topLeft(const SO4& Q, OptionalJacobian<9, 6> H) {
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if (H) {
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const Vector3 m1 = M.col(0), m2 = M.col(1), m3 = M.col(2),
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q = R.topRightCorner<3, 1>();
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*H << Z_3x1, Z_3x1, q, Z_3x1, -m3, m2, //
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Z_3x1, -q, Z_3x1, m3, Z_3x1, -m1, //
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q, Z_3x1, Z_3x1, -m2, m1, Z_3x1;
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*H << Z_3x1, Z_3x1, -q, Z_3x1, -m3, m2, //
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Z_3x1, q, Z_3x1, m3, Z_3x1, -m1, //
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-q, Z_3x1, Z_3x1, -m2, m1, Z_3x1;
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}
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return M;
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}
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@ -221,9 +222,9 @@ GTSAM_EXPORT Matrix43 stiefel(const SO4& Q, OptionalJacobian<12, 6> H) {
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const Matrix43 M = R.leftCols<3>();
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if (H) {
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const auto &m1 = R.col(0), m2 = R.col(1), m3 = R.col(2), q = R.col(3);
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*H << Z_4x1, Z_4x1, q, Z_4x1, -m3, m2, //
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Z_4x1, -q, Z_4x1, m3, Z_4x1, -m1, //
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q, Z_4x1, Z_4x1, -m2, m1, Z_4x1;
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*H << Z_4x1, Z_4x1, -q, Z_4x1, -m3, m2, //
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Z_4x1, q, Z_4x1, m3, Z_4x1, -m1, //
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-q, Z_4x1, Z_4x1, -m2, m1, Z_4x1;
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}
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return M;
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}
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@ -38,11 +38,12 @@ Matrix SOn::Hat(const Vector& xi) {
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const size_t dmin = (n - 1) * (n - 2) / 2;
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X.topLeftCorner(n - 1, n - 1) = Hat(xi.tail(dmin));
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// determine sign of last element (signs alternate)
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double sign = pow(-1.0, xi.size());
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// Now fill last row and column
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double sign = 1.0;
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for (size_t i = 0; i < n - 1; i++) {
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const size_t j = n - 2 - i;
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X(n - 1, j) = sign * xi(i);
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X(n - 1, j) = -sign * xi(i);
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X(j, n - 1) = -X(n - 1, j);
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sign = -sign;
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}
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@ -67,10 +68,10 @@ Vector SOn::Vee(const Matrix& X) {
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Vector xi(d);
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// Fill first n-1 spots from last row of X
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double sign = 1.0;
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double sign = pow(-1.0, xi.size());
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for (size_t i = 0; i < n - 1; i++) {
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const size_t j = n - 2 - i;
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xi(i) = sign * X(n - 1, j);
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xi(i) = -sign * X(n - 1, j);
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sign = -sign;
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}
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@ -24,10 +24,11 @@
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#include <Eigen/Core>
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#include <random>
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#include <iostream> // TODO(frank): how to avoid?
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#include <string>
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#include <type_traits>
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#include <vector>
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#include <random>
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namespace gtsam {
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@ -93,6 +94,16 @@ class SO : public LieGroup<SO<N>, internal::DimensionSO(N)> {
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return SO(R);
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}
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/// Named constructor from lower dimensional matrix
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template <typename Derived, int N_ = N, typename = IsDynamic<N_>>
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static SO Lift(size_t n, const Eigen::MatrixBase<Derived> &R) {
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Matrix Q = Matrix::Identity(n, n);
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size_t p = R.rows();
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assert(p < n && R.cols() == p);
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Q.topLeftCorner(p, p) = R;
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return SO(Q);
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}
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/// Construct dynamic SO(n) from Fixed SO<M>
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template <int M, int N_ = N, typename = IsDynamic<N_>>
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explicit SO(const SO<M>& R) : matrix_(R.matrix()) {}
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@ -207,11 +218,11 @@ class SO : public LieGroup<SO<N>, internal::DimensionSO(N)> {
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* etc... For example, the vector-space isomorphic to so(5) is laid out as:
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* a b c d | u v w | x y | z
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* where the latter elements correspond to "telescoping" sub-algebras:
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* 0 -z y -w d
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* z 0 -x v -c
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* -y x 0 -u b
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* w -v u 0 -a
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* -d c -b a 0
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* 0 -z y w -d
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* z 0 -x -v c
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* -y x 0 u -b
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* -w v -u 0 a
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* d -c b -a 0
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* This scheme behaves exactly as expected for SO(2) and SO(3).
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*/
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static MatrixNN Hat(const TangentVector& xi);
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@ -181,14 +181,13 @@ TEST( Rot3, retract)
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}
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/* ************************************************************************* */
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TEST(Rot3, log)
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{
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TEST(Rot3, log) {
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static const double PI = boost::math::constants::pi<double>();
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Vector w;
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Rot3 R;
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#define CHECK_OMEGA(X, Y, Z) \
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w = (Vector(3) << (double)X, (double)Y, double(Z)).finished(); \
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w = (Vector(3) << X, Y, Z).finished(); \
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R = Rot3::Rodrigues(w); \
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EXPECT(assert_equal(w, Rot3::Logmap(R), 1e-12));
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@ -230,7 +229,7 @@ TEST(Rot3, log)
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// Check 360 degree rotations
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#define CHECK_OMEGA_ZERO(X, Y, Z) \
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w = (Vector(3) << (double)X, (double)Y, double(Z)).finished(); \
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w = (Vector(3) << X, Y, Z).finished(); \
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R = Rot3::Rodrigues(w); \
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EXPECT(assert_equal((Vector)Z_3x1, Rot3::Logmap(R)));
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@ -238,6 +237,25 @@ TEST(Rot3, log)
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CHECK_OMEGA_ZERO(0, 2.0 * PI, 0)
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CHECK_OMEGA_ZERO(0, 0, 2.0 * PI)
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CHECK_OMEGA_ZERO(x * 2. * PI, y * 2. * PI, z * 2. * PI)
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// Check problematic case from Lund dataset vercingetorix.g2o
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// This is an almost rotation with determinant not *quite* 1.
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Rot3 Rlund(-0.98582676, -0.03958746, -0.16303092, //
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-0.03997006, -0.88835923, 0.45740671, //
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-0.16293753, 0.45743998, 0.87418537);
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// Rot3's Logmap returns different, but equivalent compacted
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// axis-angle vectors depending on whether Rot3 is implemented
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// by Quaternions or SO3.
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#if defined(GTSAM_USE_QUATERNIONS)
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// Quaternion bounds angle to [-pi, pi] resulting in ~179.9 degrees
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EXPECT(assert_equal(Vector3(0.264451979, -0.742197651, -3.04098211),
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(Vector)Rot3::Logmap(Rlund), 1e-8));
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#else
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// SO3 does not bound angle resulting in ~180.1 degrees
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EXPECT(assert_equal(Vector3(-0.264544406, 0.742217405, 3.04117314),
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(Vector)Rot3::Logmap(Rlund), 1e-8));
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#endif
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}
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/* ************************************************************************* */
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@ -536,16 +554,15 @@ TEST( Rot3, logmapStability ) {
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TEST(Rot3, quaternion) {
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// NOTE: This is also verifying the ability to convert Vector to Quaternion
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Quaternion q1(0.710997408193224, 0.360544029310185, 0.594459869568306, 0.105395217842782);
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Rot3 R1 = Rot3((Matrix)(Matrix(3, 3) <<
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0.271018623057411, 0.278786459830371, 0.921318086098018,
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Rot3 R1(0.271018623057411, 0.278786459830371, 0.921318086098018,
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0.578529366719085, 0.717799701969298, -0.387385285854279,
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-0.769319620053772, 0.637998195662053, 0.033250932803219).finished());
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-0.769319620053772, 0.637998195662053, 0.033250932803219);
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Quaternion q2(0.263360579192421, 0.571813128030932, 0.494678363680335, 0.599136268678053);
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Rot3 R2 = Rot3((Matrix)(Matrix(3, 3) <<
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-0.207341903877828, 0.250149415542075, 0.945745528564780,
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Quaternion q2(0.263360579192421, 0.571813128030932, 0.494678363680335,
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0.599136268678053);
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Rot3 R2(-0.207341903877828, 0.250149415542075, 0.945745528564780,
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0.881304914479026, -0.371869043667957, 0.291573424846290,
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0.424630407073532, 0.893945571198514, -0.143353873763946).finished());
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0.424630407073532, 0.893945571198514, -0.143353873763946);
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// Check creating Rot3 from quaternion
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EXPECT(assert_equal(R1, Rot3(q1)));
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@ -46,7 +46,7 @@ TEST(SOn, SO0) {
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EXPECT_LONGS_EQUAL(Eigen::Dynamic, SOn::dimension);
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EXPECT_LONGS_EQUAL(Eigen::Dynamic, SOn::Dim());
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EXPECT_LONGS_EQUAL(0, R.dim());
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EXPECT_LONGS_EQUAL(-1, traits<SOn>::GetDimension(R));
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EXPECT_LONGS_EQUAL(0, traits<SOn>::GetDimension(R));
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}
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//******************************************************************************
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@ -56,7 +56,7 @@ TEST(SOn, SO5) {
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EXPECT_LONGS_EQUAL(Eigen::Dynamic, SOn::dimension);
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EXPECT_LONGS_EQUAL(Eigen::Dynamic, SOn::Dim());
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EXPECT_LONGS_EQUAL(10, R.dim());
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EXPECT_LONGS_EQUAL(-1, traits<SOn>::GetDimension(R));
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EXPECT_LONGS_EQUAL(10, traits<SOn>::GetDimension(R));
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}
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//******************************************************************************
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@ -95,32 +95,42 @@ TEST(SOn, Random) {
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//******************************************************************************
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TEST(SOn, HatVee) {
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Vector6 v;
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v << 1, 2, 3, 4, 5, 6;
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Vector10 v;
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v << 1, 2, 3, 4, 5, 6, 7, 8, 9, 10;
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Matrix expected2(2, 2);
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expected2 << 0, -1, 1, 0;
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const auto actual2 = SOn::Hat(v.head<1>());
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CHECK(assert_equal(expected2, actual2));
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CHECK(assert_equal((Vector)v.head<1>(), SOn::Vee(actual2)));
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EXPECT(assert_equal(expected2, actual2));
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EXPECT(assert_equal((Vector)v.head<1>(), SOn::Vee(actual2)));
|
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|
||||
Matrix expected3(3, 3);
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||||
expected3 << 0, -3, 2, //
|
||||
3, 0, -1, //
|
||||
-2, 1, 0;
|
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const auto actual3 = SOn::Hat(v.head<3>());
|
||||
CHECK(assert_equal(expected3, actual3));
|
||||
CHECK(assert_equal(skewSymmetric(1, 2, 3), actual3));
|
||||
CHECK(assert_equal((Vector)v.head<3>(), SOn::Vee(actual3)));
|
||||
EXPECT(assert_equal(expected3, actual3));
|
||||
EXPECT(assert_equal(skewSymmetric(1, 2, 3), actual3));
|
||||
EXPECT(assert_equal((Vector)v.head<3>(), SOn::Vee(actual3)));
|
||||
|
||||
Matrix expected4(4, 4);
|
||||
expected4 << 0, -6, 5, -3, //
|
||||
6, 0, -4, 2, //
|
||||
-5, 4, 0, -1, //
|
||||
3, -2, 1, 0;
|
||||
const auto actual4 = SOn::Hat(v);
|
||||
CHECK(assert_equal(expected4, actual4));
|
||||
CHECK(assert_equal((Vector)v, SOn::Vee(actual4)));
|
||||
expected4 << 0, -6, 5, 3, //
|
||||
6, 0, -4, -2, //
|
||||
-5, 4, 0, 1, //
|
||||
-3, 2, -1, 0;
|
||||
const auto actual4 = SOn::Hat(v.head<6>());
|
||||
EXPECT(assert_equal(expected4, actual4));
|
||||
EXPECT(assert_equal((Vector)v.head<6>(), SOn::Vee(actual4)));
|
||||
|
||||
Matrix expected5(5, 5);
|
||||
expected5 << 0,-10, 9, 7, -4, //
|
||||
10, 0, -8, -6, 3, //
|
||||
-9, 8, 0, 5, -2, //
|
||||
-7, 6, -5, 0, 1, //
|
||||
4, -3, 2, -1, 0;
|
||||
const auto actual5 = SOn::Hat(v);
|
||||
EXPECT(assert_equal(expected5, actual5));
|
||||
EXPECT(assert_equal((Vector)v, SOn::Vee(actual5)));
|
||||
}
|
||||
|
||||
//******************************************************************************
|
||||
|
|
|
|||
Loading…
Reference in New Issue