Switched to struct with static methods as apparently global methods in namespaces are not wrapped.
Frank Dellaert
parent
3a371a1cf2
commit
e2cf42773a
21
gtsam.h
21
gtsam.h
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@ -2524,21 +2524,24 @@ class BetweenFactorPose3s
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};
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#include <gtsam/slam/InitializePose3.h>
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namespace initialize_pose3 {
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gtsam::Values computeOrientationsChordal(
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class InitializePose3 {
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static gtsam::Values computeOrientationsChordal(
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const gtsam::NonlinearFactorGraph& pose3Graph);
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gtsam::Values computeOrientationsGradient(
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static gtsam::Values computeOrientationsGradient(
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const gtsam::NonlinearFactorGraph& pose3Graph,
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const gtsam::Values& givenGuess, size_t maxIter, const bool setRefFrame);
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gtsam::Values computeOrientationsGradient(
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static gtsam::Values computeOrientationsGradient(
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const gtsam::NonlinearFactorGraph& pose3Graph,
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const gtsam::Values& givenGuess);
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gtsam::NonlinearFactorGraph buildPose3graph(
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static gtsam::NonlinearFactorGraph buildPose3graph(
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const gtsam::NonlinearFactorGraph& graph);
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gtsam::Values initialize(const gtsam::NonlinearFactorGraph& graph,
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const gtsam::Values& givenGuess, bool useGradient);
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gtsam::Values initialize(const gtsam::NonlinearFactorGraph& graph);
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} // namespace initialize_pose3
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static gtsam::Values initializeOrientations(
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const gtsam::NonlinearFactorGraph& graph);
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static gtsam::Values initialize(const gtsam::NonlinearFactorGraph& graph,
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const gtsam::Values& givenGuess,
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bool useGradient);
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static gtsam::Values initialize(const gtsam::NonlinearFactorGraph& graph);
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};
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gtsam::BetweenFactorPose3s parse3DFactors(string filename);
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pair<gtsam::NonlinearFactorGraph*, gtsam::Values*> load3D(string filename);
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@ -29,12 +29,11 @@
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using namespace std;
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namespace gtsam {
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namespace initialize_pose3 {
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static const Key kAnchorKey = symbol('Z', 9999999);
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/* ************************************************************************* */
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GaussianFactorGraph buildLinearOrientationGraph(const NonlinearFactorGraph& g) {
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GaussianFactorGraph InitializePose3::buildLinearOrientationGraph(const NonlinearFactorGraph& g) {
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GaussianFactorGraph linearGraph;
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noiseModel::Unit::shared_ptr model = noiseModel::Unit::Create(9);
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@ -67,7 +66,8 @@ GaussianFactorGraph buildLinearOrientationGraph(const NonlinearFactorGraph& g) {
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/* ************************************************************************* */
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// Transform VectorValues into valid Rot3
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Values normalizeRelaxedRotations(const VectorValues& relaxedRot3) {
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Values InitializePose3::normalizeRelaxedRotations(
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const VectorValues& relaxedRot3) {
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gttic(InitializePose3_computeOrientationsChordal);
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Matrix ppm = Z_3x3; // plus plus minus
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@ -94,7 +94,7 @@ Values normalizeRelaxedRotations(const VectorValues& relaxedRot3) {
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}
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/* ************************************************************************* */
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NonlinearFactorGraph buildPose3graph(const NonlinearFactorGraph& graph) {
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NonlinearFactorGraph InitializePose3::buildPose3graph(const NonlinearFactorGraph& graph) {
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gttic(InitializePose3_buildPose3graph);
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NonlinearFactorGraph pose3Graph;
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@ -115,7 +115,8 @@ NonlinearFactorGraph buildPose3graph(const NonlinearFactorGraph& graph) {
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}
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/* ************************************************************************* */
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Values computeOrientationsChordal(const NonlinearFactorGraph& pose3Graph) {
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Values InitializePose3::computeOrientationsChordal(
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const NonlinearFactorGraph& pose3Graph) {
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gttic(InitializePose3_computeOrientationsChordal);
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// regularize measurements and plug everything in a factor graph
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@ -129,10 +130,9 @@ Values computeOrientationsChordal(const NonlinearFactorGraph& pose3Graph) {
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}
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/* ************************************************************************* */
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Values computeOrientationsGradient(const NonlinearFactorGraph& pose3Graph,
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const Values& givenGuess,
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const size_t maxIter,
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const bool setRefFrame) {
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Values InitializePose3::computeOrientationsGradient(
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const NonlinearFactorGraph& pose3Graph, const Values& givenGuess,
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const size_t maxIter, const bool setRefFrame) {
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gttic(InitializePose3_computeOrientationsGradient);
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// this works on the inverse rotations, according to Tron&Vidal,2011
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@ -231,7 +231,7 @@ Values computeOrientationsGradient(const NonlinearFactorGraph& pose3Graph,
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}
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/* ************************************************************************* */
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void createSymbolicGraph(KeyVectorMap& adjEdgesMap, KeyRotMap& factorId2RotMap,
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void InitializePose3::createSymbolicGraph(KeyVectorMap& adjEdgesMap, KeyRotMap& factorId2RotMap,
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const NonlinearFactorGraph& pose3Graph) {
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size_t factorId = 0;
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for(const auto& factor: pose3Graph) {
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@ -264,7 +264,7 @@ void createSymbolicGraph(KeyVectorMap& adjEdgesMap, KeyRotMap& factorId2RotMap,
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}
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/* ************************************************************************* */
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Vector3 gradientTron(const Rot3& R1, const Rot3& R2, const double a, const double b) {
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Vector3 InitializePose3::gradientTron(const Rot3& R1, const Rot3& R2, const double a, const double b) {
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Vector3 logRot = Rot3::Logmap(R1.between(R2));
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double th = logRot.norm();
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@ -286,8 +286,7 @@ Vector3 gradientTron(const Rot3& R1, const Rot3& R2, const double a, const doubl
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}
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/* ************************************************************************* */
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Values initializeOrientations(const NonlinearFactorGraph& graph) {
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Values InitializePose3::initializeOrientations(const NonlinearFactorGraph& graph) {
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// We "extract" the Pose3 subgraph of the original graph: this
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// is done to properly model priors and avoiding operating on a larger graph
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NonlinearFactorGraph pose3Graph = buildPose3graph(graph);
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@ -297,7 +296,7 @@ Values initializeOrientations(const NonlinearFactorGraph& graph) {
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}
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///* ************************************************************************* */
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Values computePoses(NonlinearFactorGraph& pose3graph, Values& initialRot) {
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Values InitializePose3::computePoses(NonlinearFactorGraph& pose3graph, Values& initialRot) {
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gttic(InitializePose3_computePoses);
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// put into Values structure
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@ -339,7 +338,7 @@ Values computePoses(NonlinearFactorGraph& pose3graph, Values& initialRot) {
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}
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/* ************************************************************************* */
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Values initialize(const NonlinearFactorGraph& graph, const Values& givenGuess,
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Values InitializePose3::initialize(const NonlinearFactorGraph& graph, const Values& givenGuess,
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bool useGradient) {
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gttic(InitializePose3_initialize);
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Values initialValues;
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@ -360,9 +359,8 @@ Values initialize(const NonlinearFactorGraph& graph, const Values& givenGuess,
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}
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/* ************************************************************************* */
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Values initialize(const NonlinearFactorGraph& graph) {
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Values InitializePose3::initialize(const NonlinearFactorGraph& graph) {
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return initialize(graph, Values(), false);
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}
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} // namespace initialize_pose3
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} // namespace gtsam
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@ -31,54 +31,57 @@ namespace gtsam {
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typedef std::map<Key, std::vector<size_t> > KeyVectorMap;
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typedef std::map<Key, Rot3> KeyRotMap;
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namespace initialize_pose3 {
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struct GTSAM_EXPORT InitializePose3 {
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static GaussianFactorGraph buildLinearOrientationGraph(
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const NonlinearFactorGraph& g);
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GTSAM_EXPORT GaussianFactorGraph
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buildLinearOrientationGraph(const NonlinearFactorGraph& g);
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static Values normalizeRelaxedRotations(const VectorValues& relaxedRot3);
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GTSAM_EXPORT Values normalizeRelaxedRotations(const VectorValues& relaxedRot3);
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/**
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/**
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* Return the orientations of a graph including only BetweenFactors<Pose3>
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*/
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GTSAM_EXPORT Values
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computeOrientationsChordal(const NonlinearFactorGraph& pose3Graph);
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static Values computeOrientationsChordal(
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const NonlinearFactorGraph& pose3Graph);
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/**
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/**
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* Return the orientations of a graph including only BetweenFactors<Pose3>
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*/
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GTSAM_EXPORT Values computeOrientationsGradient(
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static Values computeOrientationsGradient(
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const NonlinearFactorGraph& pose3Graph, const Values& givenGuess,
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size_t maxIter = 10000, const bool setRefFrame = true);
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GTSAM_EXPORT void createSymbolicGraph(KeyVectorMap& adjEdgesMap,
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static void createSymbolicGraph(KeyVectorMap& adjEdgesMap,
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KeyRotMap& factorId2RotMap,
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const NonlinearFactorGraph& pose3Graph);
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GTSAM_EXPORT Vector3 gradientTron(const Rot3& R1, const Rot3& R2,
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const double a, const double b);
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static Vector3 gradientTron(const Rot3& R1, const Rot3& R2, const double a,
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const double b);
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/**
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* Select the subgraph of betweenFactors and transforms priors into between wrt
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* a fictitious node
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/**
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* Select the subgraph of betweenFactors and transforms priors into between
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* wrt a fictitious node
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*/
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GTSAM_EXPORT NonlinearFactorGraph
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buildPose3graph(const NonlinearFactorGraph& graph);
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static NonlinearFactorGraph buildPose3graph(
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const NonlinearFactorGraph& graph);
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GTSAM_EXPORT Values computePoses(NonlinearFactorGraph& pose3graph,
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static Values computePoses(NonlinearFactorGraph& pose3graph,
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Values& initialRot);
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/**
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/**
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* "extract" the Pose3 subgraph of the original graph, get orientations from
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* relative orientation measurements (using either gradient or chordal method),
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* and finish up with 1 GN iteration on full poses.
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* relative orientation measurements using chordal method.
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*/
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GTSAM_EXPORT Values initialize(const NonlinearFactorGraph& graph,
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const Values& givenGuess,
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bool useGradient = false);
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static Values initializeOrientations(const NonlinearFactorGraph& graph);
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/// Calls initialize above using Chordal method.
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GTSAM_EXPORT Values initialize(const NonlinearFactorGraph& graph);
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/**
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* "extract" the Pose3 subgraph of the original graph, get orientations from
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* relative orientation measurements (using either gradient or chordal
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* method), and finish up with 1 GN iteration on full poses.
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*/
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static Values initialize(const NonlinearFactorGraph& graph,
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const Values& givenGuess, bool useGradient = false);
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} // namespace initialize_pose3
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/// Calls initialize above using Chordal method.
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static Values initialize(const NonlinearFactorGraph& graph);
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};
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} // end of namespace gtsam
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@ -74,15 +74,15 @@ NonlinearFactorGraph graph() {
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/* *************************************************************************** */
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TEST( InitializePose3, buildPose3graph ) {
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NonlinearFactorGraph pose3graph = initialize_pose3::buildPose3graph(simple::graph());
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NonlinearFactorGraph pose3graph = InitializePose3::buildPose3graph(simple::graph());
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// pose3graph.print("");
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}
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/* *************************************************************************** */
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TEST( InitializePose3, orientations ) {
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NonlinearFactorGraph pose3Graph = initialize_pose3::buildPose3graph(simple::graph());
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NonlinearFactorGraph pose3Graph = InitializePose3::buildPose3graph(simple::graph());
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Values initial = initialize_pose3::computeOrientationsChordal(pose3Graph);
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Values initial = InitializePose3::computeOrientationsChordal(pose3Graph);
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// comparison is up to M_PI, that's why we add some multiples of 2*M_PI
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EXPECT(assert_equal(simple::R0, initial.at<Rot3>(x0), 1e-6));
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@ -93,12 +93,12 @@ TEST( InitializePose3, orientations ) {
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/* *************************************************************************** */
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TEST( InitializePose3, orientationsGradientSymbolicGraph ) {
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NonlinearFactorGraph pose3Graph = initialize_pose3::buildPose3graph(simple::graph());
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NonlinearFactorGraph pose3Graph = InitializePose3::buildPose3graph(simple::graph());
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KeyVectorMap adjEdgesMap;
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KeyRotMap factorId2RotMap;
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initialize_pose3::createSymbolicGraph(adjEdgesMap, factorId2RotMap, pose3Graph);
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InitializePose3::createSymbolicGraph(adjEdgesMap, factorId2RotMap, pose3Graph);
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EXPECT_DOUBLES_EQUAL(adjEdgesMap.at(x0)[0], 0, 1e-9);
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EXPECT_DOUBLES_EQUAL(adjEdgesMap.at(x0)[1], 3, 1e-9);
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@ -132,7 +132,7 @@ TEST( InitializePose3, singleGradient ) {
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double a = 6.010534238540223;
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double b = 1.0;
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Vector actual = initialize_pose3::gradientTron(R1, R2, a, b);
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Vector actual = InitializePose3::gradientTron(R1, R2, a, b);
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Vector expected = Vector3::Zero();
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expected(2) = 1.962658662803917;
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@ -142,7 +142,7 @@ TEST( InitializePose3, singleGradient ) {
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/* *************************************************************************** */
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TEST( InitializePose3, iterationGradient ) {
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NonlinearFactorGraph pose3Graph = initialize_pose3::buildPose3graph(simple::graph());
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NonlinearFactorGraph pose3Graph = InitializePose3::buildPose3graph(simple::graph());
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// Wrong initial guess - initialization should fix the rotations
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Rot3 Rpert = Rot3::Expmap(Vector3(0.01, 0.01, 0.01));
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@ -154,7 +154,7 @@ TEST( InitializePose3, iterationGradient ) {
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size_t maxIter = 1; // test gradient at the first iteration
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bool setRefFrame = false;
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Values orientations = initialize_pose3::computeOrientationsGradient(pose3Graph, givenPoses, maxIter, setRefFrame);
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Values orientations = InitializePose3::computeOrientationsGradient(pose3Graph, givenPoses, maxIter, setRefFrame);
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Matrix M0 = (Matrix(3,3) << 0.999435813876064, -0.033571481675497, 0.001004768630281,
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0.033572116359134, 0.999436104312325, -0.000621610948719,
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@ -183,7 +183,7 @@ TEST( InitializePose3, iterationGradient ) {
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/* *************************************************************************** */
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TEST( InitializePose3, orientationsGradient ) {
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NonlinearFactorGraph pose3Graph = initialize_pose3::buildPose3graph(simple::graph());
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NonlinearFactorGraph pose3Graph = InitializePose3::buildPose3graph(simple::graph());
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// Wrong initial guess - initialization should fix the rotations
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Rot3 Rpert = Rot3::Expmap(Vector3(0.01, 0.01, 0.01));
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@ -194,7 +194,7 @@ TEST( InitializePose3, orientationsGradient ) {
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givenPoses.insert(x3, (simple::pose0).compose( Pose3(Rpert,Point3(0,0,0)) ));
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// do 10 gradient iterations
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bool setRefFrame = false;
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Values orientations = initialize_pose3::computeOrientationsGradient(pose3Graph, givenPoses, 10, setRefFrame);
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Values orientations = InitializePose3::computeOrientationsGradient(pose3Graph, givenPoses, 10, setRefFrame);
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// const Key keyAnchor = symbol('Z', 9999999);
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// givenPoses.insert(keyAnchor,simple::pose0);
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@ -228,7 +228,7 @@ TEST( InitializePose3, posesWithGivenGuess ) {
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givenPoses.insert(x2,simple::pose2);
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givenPoses.insert(x3,simple::pose3);
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Values initial = initialize_pose3::initialize(simple::graph(), givenPoses);
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Values initial = InitializePose3::initialize(simple::graph(), givenPoses);
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// comparison is up to M_PI, that's why we add some multiples of 2*M_PI
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EXPECT(assert_equal(givenPoses, initial, 1e-6));
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@ -245,7 +245,7 @@ TEST( InitializePose3, initializePoses )
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noiseModel::Unit::shared_ptr priorModel = noiseModel::Unit::Create(6);
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inputGraph->add(PriorFactor<Pose3>(0, Pose3(), priorModel));
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Values initial = initialize_pose3::initialize(*inputGraph);
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Values initial = InitializePose3::initialize(*inputGraph);
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EXPECT(assert_equal(*expectedValues,initial,0.1)); // TODO(frank): very loose !!
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}
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