Rotation works, translation and scale incorrect
parent
d28ef19b9a
commit
a87a3dd987
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@ -91,12 +91,13 @@ public:
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return R_ * (s_ * p) + t_;
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return R_ * (s_ * p) + t_;
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}
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}
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Matrix7 adjointMap() const{
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Matrix7 AdjointMap() const{
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const Matrix3 R = R_.matrix();
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const Matrix3 R = R_.matrix();
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const Vector3 t = t_.vector();
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const Vector3 t = t_.vector();
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Matrix3 A = s_ * skewSymmetric(t) * R;
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Matrix3 A = s_ * skewSymmetric(t) * R;
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Matrix7 adj;
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Matrix7 adj;
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adj << s_*R, A, -s_*t, Z_3x3, R, Eigen::Matrix<double, 3, 1>::Zero(), Z_3x3, Z_3x3, 1;
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adj << s_*R, A, -s_*t, Z_3x3, R, Eigen::Matrix<double, 3, 1>::Zero(), Z_3x3, Z_3x3, 1;
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return adj;
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}
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}
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/** syntactic sugar for transform_from */
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/** syntactic sugar for transform_from */
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@ -104,16 +105,18 @@ public:
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return transform_from(p);
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return transform_from(p);
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}
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}
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/*Similarity3 inverse() const {
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Similarity3 inverse() const {
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Rot3 Rt = R_.inverse();
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Rot3 Rt = R_.inverse();
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return Pose3(Rt, Rt * (-t_));
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Point3 sRt = R_.inverse() * (s_ * t_);
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}*/
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return Similarity3(Rt, sRt, 1.0/s_);
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}
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Similarity3 operator*(const Similarity3& T) const {
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Similarity3 operator*(const Similarity3& T) const {
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return Similarity3(R_ * T.R_, ((1.0/s_)*t_) + R_ * T.t_, s_*T.s_);
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return Similarity3(R_ * T.R_, ((1.0/s_)*t_) + R_ * T.t_, s_*T.s_);
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}
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}
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void print(const std::string& s) const {
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void print(const std::string& s) const {
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std::cout << std::endl;
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std::cout << s;
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std::cout << s;
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rotation().print("R:\n");
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rotation().print("R:\n");
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translation().print("t: ");
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translation().print("t: ");
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@ -149,26 +152,31 @@ public:
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}
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}
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/// Update Similarity transform via 7-dim vector in tangent space
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/// Update Similarity transform via 7-dim vector in tangent space
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/* Similarity3 retract(const Vector7& v) const {
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struct ChartAtOrigin {
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static Similarity3 Retract(const Vector7& v, ChartJacobian H = boost::none) {
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// Will retracting or localCoordinating R work if R is not a unit rotation?
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// Will retracting or localCoordinating R work if R is not a unit rotation?
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// Also, how do we actually get s out? Seems like we need to store it somewhere.
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// Also, how do we actually get s out? Seems like we need to store it somewhere.
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Rot3 r; //Create a zero rotation to do our retraction.
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return Similarity3( //
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return Similarity3( //
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R_.retract(v.head<3>()), // retract rotation using v[0,1,2]
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r.retract(v.head<3>()), // retract rotation using v[0,1,2]
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t_.retract(R() * v.segment<3>(3)), // Retract the translation
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Point3(v.segment<3>(3)), // Retract the translation
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scale() + v[6]); //finally, update scale using v[6]
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v[6]); //finally, update scale using v[6]
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}
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}
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/// 7-dimensional vector v in tangent space that makes other = this->retract(v)
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/// 7-dimensional vector v in tangent space that makes other = this->retract(v)
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Vector7 localCoordinates(const Similarity3& other) const {
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static Vector7 Local(const Similarity3& other, ChartJacobian H = boost::none) {
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Rot3 r; //Create a zero rotation to do the retraction
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Vector7 v;
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Vector7 v;
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v.head<3>() = R_.localCoordinates(other.R_);
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v.head<3>() = r.localCoordinates(other.R_);
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v.segment<3>(3) = R_.unrotate(other.t_ - t_).vector();
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v.segment<3>(3) = other.t_.vector();
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//v.segment<3>(3) = translation().localCoordinates(other.translation());
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//v.segment<3>(3) = translation().localCoordinates(other.translation());
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v[6] = other.s_ - s_;
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v[6] = other.s_;
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return v;
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return v;
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}*/
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}
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};
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using LieGroup<Similarity3, 7>::inverse; // version with derivative
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/// @}
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/// @}
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@ -200,7 +208,7 @@ struct traits<Similarity3> : public internal::LieGroupTraits<Similarity3> {};
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using namespace gtsam;
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using namespace gtsam;
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using namespace std;
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using namespace std;
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//GTSAM_CONCEPT_POSE_INST(Similarity3);
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GTSAM_CONCEPT_TESTABLE_INST(Similarity3)
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static Point3 P(0.2,0.7,-2);
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static Point3 P(0.2,0.7,-2);
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static Rot3 R = Rot3::rodriguez(0.3,0,0);
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static Rot3 R = Rot3::rodriguez(0.3,0,0);
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@ -299,24 +307,23 @@ TEST(Similarity3, manifold_first_order)
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TEST(Similarity3, Optimization) {
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TEST(Similarity3, Optimization) {
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Similarity3 prior = Similarity3(Rot3::ypr(0.1, 0.2, 0.3), Point3(1, 2, 3), 4);
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Similarity3 prior = Similarity3(Rot3::ypr(0.1, 0.2, 0.3), Point3(1, 2, 3), 4);
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prior.print("goal angle");
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prior.print("Goal Transform");
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noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(7, 1);
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noiseModel::Isotropic::shared_ptr model = noiseModel::Isotropic::Sigma(7, 1);
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Symbol key('x',1);
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Symbol key('x',1);
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Symbol key2('x',2);
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PriorFactor<Similarity3> factor(key, prior, model);
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PriorFactor<Similarity3> factor(key, prior, model);
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NonlinearFactorGraph graph;
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NonlinearFactorGraph graph;
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graph.push_back(factor);
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graph.push_back(factor);
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graph.print("full graph");
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graph.print("Full Graph");
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Values initial;
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Values initial;
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initial.insert<Similarity3>(key, Similarity3());
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initial.insert<Similarity3>(key, Similarity3());
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initial.print("initial estimate");
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initial.print("Initial Estimate");
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Values result;
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Values result;
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result.insert(key2, LevenbergMarquardtOptimizer(graph, initial).optimize());
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result = LevenbergMarquardtOptimizer(graph, initial).optimize();
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result.print("final result");
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result.print("Optimized Estimate");
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EXPECT(assert_equal(prior, result.at<Similarity3>(key2), 1e-2));
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EXPECT(assert_equal(prior, result.at<Similarity3>(key)));
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}
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}
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