Modernized, documented
Frank Dellaert
parent
9a16cf97a7
commit
37eba50932
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@ -29,13 +29,9 @@
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using namespace std;
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namespace gtsam {
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namespace InitializePose3 {
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namespace initialize_pose3 {
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static const Matrix I9 = I_9x9;
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static const Vector zero9 = Vector::Zero(9);
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static const Matrix zero33 = Z_3x3;
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static const Key keyAnchor = symbol('Z', 9999999);
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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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@ -43,26 +39,29 @@ GaussianFactorGraph 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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for(const boost::shared_ptr<NonlinearFactor>& factor: g) {
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for(const auto& factor: g) {
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Matrix3 Rij;
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boost::shared_ptr<BetweenFactor<Pose3> > pose3Between =
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boost::dynamic_pointer_cast<BetweenFactor<Pose3> >(factor);
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auto pose3Between = boost::dynamic_pointer_cast<BetweenFactor<Pose3> >(factor);
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if (pose3Between)
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Rij = pose3Between->measured().rotation().matrix();
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else
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std::cout << "Error in buildLinearOrientationGraph" << std::endl;
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cout << "Error in buildLinearOrientationGraph" << endl;
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const KeyVector& keys = factor->keys();
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const auto& keys = factor->keys();
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Key key1 = keys[0], key2 = keys[1];
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Matrix M9 = Z_9x9;
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M9.block(0,0,3,3) = Rij;
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M9.block(3,3,3,3) = Rij;
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M9.block(6,6,3,3) = Rij;
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linearGraph.add(key1, -I9, key2, M9, zero9, model);
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linearGraph.add(key1, -I_9x9, key2, M9, Z_9x1, model);
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}
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// prior on the anchor orientation
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linearGraph.add(keyAnchor, I9, (Vector(9) << 1.0, 0.0, 0.0,/* */ 0.0, 1.0, 0.0, /* */ 0.0, 0.0, 1.0).finished(), model);
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linearGraph.add(
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kAnchorKey, I_9x9,
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(Vector(9) << 1.0, 0.0, 0.0, /* */ 0.0, 1.0, 0.0, /* */ 0.0, 0.0, 1.0)
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.finished(),
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model);
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return linearGraph;
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}
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@ -75,23 +74,15 @@ Values normalizeRelaxedRotations(const VectorValues& relaxedRot3) {
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ppm(0,0) = 1; ppm(1,1) = 1; ppm(2,2) = -1;
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Values validRot3;
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for(const VectorValues::value_type& it: relaxedRot3) {
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for(const auto& it: relaxedRot3) {
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Key key = it.first;
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if (key != keyAnchor) {
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const Vector& rotVector = it.second;
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Matrix3 rotMat;
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rotMat(0,0) = rotVector(0); rotMat(0,1) = rotVector(1); rotMat(0,2) = rotVector(2);
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rotMat(1,0) = rotVector(3); rotMat(1,1) = rotVector(4); rotMat(1,2) = rotVector(5);
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rotMat(2,0) = rotVector(6); rotMat(2,1) = rotVector(7); rotMat(2,2) = rotVector(8);
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if (key != kAnchorKey) {
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Matrix3 R; R << it.second;
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Matrix U, V; Vector s;
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svd(rotMat, U, s, V);
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svd(R.transpose(), U, s, V);
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Matrix3 normalizedRotMat = U * V.transpose();
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// std::cout << "rotMat \n" << rotMat << std::endl;
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// std::cout << "U V' \n" << U * V.transpose() << std::endl;
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// std::cout << "V \n" << V << std::endl;
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if(normalizedRotMat.determinant() < 0)
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normalizedRotMat = U * ppm * V.transpose();
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@ -103,31 +94,27 @@ Values normalizeRelaxedRotations(const VectorValues& relaxedRot3) {
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}
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/* ************************************************************************* */
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// Select the subgraph of betweenFactors and transforms priors into between wrt a fictitious node
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NonlinearFactorGraph buildPose3graph(const NonlinearFactorGraph& graph) {
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gttic(InitializePose3_buildPose3graph);
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NonlinearFactorGraph pose3Graph;
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for(const boost::shared_ptr<NonlinearFactor>& factor: graph) {
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for(const auto& factor: graph) {
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// recast to a between on Pose3
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boost::shared_ptr<BetweenFactor<Pose3> > pose3Between =
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boost::dynamic_pointer_cast<BetweenFactor<Pose3> >(factor);
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const auto pose3Between = boost::dynamic_pointer_cast<BetweenFactor<Pose3> >(factor);
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if (pose3Between)
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pose3Graph.add(pose3Between);
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// recast PriorFactor<Pose3> to BetweenFactor<Pose3>
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boost::shared_ptr<PriorFactor<Pose3> > pose3Prior =
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boost::dynamic_pointer_cast<PriorFactor<Pose3> >(factor);
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const auto pose3Prior = boost::dynamic_pointer_cast<PriorFactor<Pose3> >(factor);
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if (pose3Prior)
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pose3Graph.emplace_shared<BetweenFactor<Pose3> >(keyAnchor, pose3Prior->keys()[0],
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pose3Graph.emplace_shared<BetweenFactor<Pose3> >(kAnchorKey, pose3Prior->keys()[0],
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pose3Prior->prior(), pose3Prior->noiseModel());
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}
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return 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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Values computeOrientationsChordal(const NonlinearFactorGraph& pose3Graph) {
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gttic(InitializePose3_computeOrientationsChordal);
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@ -142,14 +129,16 @@ Values computeOrientationsChordal(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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Values computeOrientationsGradient(const NonlinearFactorGraph& pose3Graph, const Values& givenGuess, const size_t maxIter, const bool setRefFrame) {
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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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gttic(InitializePose3_computeOrientationsGradient);
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// this works on the inverse rotations, according to Tron&Vidal,2011
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Values inverseRot;
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inverseRot.insert(keyAnchor, Rot3());
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for(const Values::ConstKeyValuePair& key_value: givenGuess) {
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inverseRot.insert(kAnchorKey, Rot3());
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for(const auto& key_value: givenGuess) {
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Key key = key_value.key;
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const Pose3& pose = givenGuess.at<Pose3>(key);
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inverseRot.insert(key, pose.rotation().inverse());
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@ -164,9 +153,9 @@ Values computeOrientationsGradient(const NonlinearFactorGraph& pose3Graph, const
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// calculate max node degree & allocate gradient
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size_t maxNodeDeg = 0;
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VectorValues grad;
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for(const Values::ConstKeyValuePair& key_value: inverseRot) {
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for(const auto& key_value: inverseRot) {
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Key key = key_value.key;
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grad.insert(key,Vector3::Zero());
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grad.insert(key,Z_3x1);
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size_t currNodeDeg = (adjEdgesMap.at(key)).size();
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if(currNodeDeg > maxNodeDeg)
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maxNodeDeg = currNodeDeg;
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@ -180,42 +169,37 @@ Values computeOrientationsGradient(const NonlinearFactorGraph& pose3Graph, const
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double mu_max = maxNodeDeg * rho;
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double stepsize = 2/mu_max; // = 1/(a b dG)
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std::cout <<" b " << b <<" f0 " << f0 <<" a " << a <<" rho " << rho <<" stepsize " << stepsize << " maxNodeDeg "<< maxNodeDeg << std::endl;
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double maxGrad;
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// gradient iterations
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size_t it;
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for(it=0; it < maxIter; it++){
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for (it = 0; it < maxIter; it++) {
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//////////////////////////////////////////////////////////////////////////
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// compute the gradient at each node
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//std::cout << "it " << it <<" b " << b <<" f0 " << f0 <<" a " << a
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// <<" rho " << rho <<" stepsize " << stepsize << " maxNodeDeg "<< maxNodeDeg << std::endl;
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maxGrad = 0;
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for(const Values::ConstKeyValuePair& key_value: inverseRot) {
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for (const auto& key_value : inverseRot) {
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Key key = key_value.key;
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//std::cout << "---------------------------key " << DefaultKeyFormatter(key) << std::endl;
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Vector gradKey = Vector3::Zero();
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Vector gradKey = Z_3x1;
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// collect the gradient for each edge incident on key
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for(const size_t& factorId: adjEdgesMap.at(key)){
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for (const size_t& factorId : adjEdgesMap.at(key)) {
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Rot3 Rij = factorId2RotMap.at(factorId);
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Rot3 Ri = inverseRot.at<Rot3>(key);
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if( key == (pose3Graph.at(factorId))->keys()[0] ){
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Key key1 = (pose3Graph.at(factorId))->keys()[1];
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auto factor = pose3Graph.at(factorId);
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const auto& keys = factor->keys();
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if (key == keys[0]) {
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Key key1 = keys[1];
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Rot3 Rj = inverseRot.at<Rot3>(key1);
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gradKey = gradKey + gradientTron(Ri, Rij * Rj, a, b);
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//std::cout << "key1 " << DefaultKeyFormatter(key1) << " gradientTron(Ri, Rij * Rj, a, b) \n " << gradientTron(Ri, Rij * Rj, a, b) << std::endl;
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}else if( key == (pose3Graph.at(factorId))->keys()[1] ){
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Key key0 = (pose3Graph.at(factorId))->keys()[0];
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} else if (key == keys[1]) {
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Key key0 = keys[0];
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Rot3 Rj = inverseRot.at<Rot3>(key0);
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gradKey = gradKey + gradientTron(Ri, Rij.between(Rj), a, b);
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//std::cout << "key0 " << DefaultKeyFormatter(key0) << " gradientTron(Ri, Rij.inverse() * Rj, a, b) \n " << gradientTron(Ri, Rij.between(Rj), a, b) << std::endl;
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}else{
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std::cout << "Error in gradient computation" << std::endl;
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} else {
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cout << "Error in gradient computation" << endl;
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}
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} // end of i-th gradient computation
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grad.at(key) = stepsize * gradKey;
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double normGradKey = (gradKey).norm();
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//std::cout << "key " << DefaultKeyFormatter(key) <<" \n grad \n" << grad.at(key) << std::endl;
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if(normGradKey>maxGrad)
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maxGrad = normGradKey;
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} // end of loop over nodes
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@ -230,14 +214,12 @@ Values computeOrientationsGradient(const NonlinearFactorGraph& pose3Graph, const
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break;
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} // enf of gradient iterations
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std::cout << "nr of gradient iterations " << it << "maxGrad " << maxGrad << std::endl;
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// Return correct rotations
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const Rot3& Rref = inverseRot.at<Rot3>(keyAnchor); // This will be set to the identity as so far we included no prior
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const Rot3& Rref = inverseRot.at<Rot3>(kAnchorKey); // This will be set to the identity as so far we included no prior
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Values estimateRot;
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for(const Values::ConstKeyValuePair& key_value: inverseRot) {
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for(const auto& key_value: inverseRot) {
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Key key = key_value.key;
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if (key != keyAnchor) {
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if (key != kAnchorKey) {
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const Rot3& R = inverseRot.at<Rot3>(key);
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if(setRefFrame)
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estimateRot.insert(key, Rref.compose(R.inverse()));
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@ -249,11 +231,11 @@ Values computeOrientationsGradient(const NonlinearFactorGraph& pose3Graph, const
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}
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/* ************************************************************************* */
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void createSymbolicGraph(KeyVectorMap& adjEdgesMap, KeyRotMap& factorId2RotMap, const NonlinearFactorGraph& pose3Graph){
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void 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 boost::shared_ptr<NonlinearFactor>& factor: pose3Graph) {
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boost::shared_ptr<BetweenFactor<Pose3> > pose3Between =
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boost::dynamic_pointer_cast<BetweenFactor<Pose3> >(factor);
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for(const auto& factor: pose3Graph) {
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auto pose3Between = boost::dynamic_pointer_cast<BetweenFactor<Pose3> >(factor);
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if (pose3Between){
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Rot3 Rij = pose3Between->measured().rotation();
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factorId2RotMap.insert(pair<Key, Rot3 >(factorId,Rij));
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@ -275,7 +257,7 @@ void createSymbolicGraph(KeyVectorMap& adjEdgesMap, KeyRotMap& factorId2RotMap,
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adjEdgesMap.insert(pair<Key, vector<size_t> >(key2, edge_id));
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}
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}else{
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std::cout << "Error in computeOrientationsGradient" << std::endl;
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cout << "Error in createSymbolicGraph" << endl;
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}
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factorId++;
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}
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@ -292,10 +274,10 @@ Vector3 gradientTron(const Rot3& R1, const Rot3& R2, const double a, const doubl
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th = logRot.norm();
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}
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// exclude small or invalid rotations
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if (th > 1e-5 && th == th){ // nonzero valid rotations
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if (th > 1e-5 && th == th) { // nonzero valid rotations
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logRot = logRot / th;
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}else{
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logRot = Vector3::Zero();
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} else {
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logRot = Z_3x1;
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th = 0.0;
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}
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@ -320,24 +302,25 @@ Values computePoses(NonlinearFactorGraph& pose3graph, Values& initialRot) {
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// put into Values structure
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Values initialPose;
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for(const Values::ConstKeyValuePair& key_value: initialRot){
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for (const auto& key_value : initialRot) {
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Key key = key_value.key;
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const Rot3& rot = initialRot.at<Rot3>(key);
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Pose3 initializedPose = Pose3(rot, Point3(0, 0, 0));
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initialPose.insert(key, initializedPose);
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}
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// add prior
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noiseModel::Unit::shared_ptr priorModel = noiseModel::Unit::Create(6);
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initialPose.insert(keyAnchor, Pose3());
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pose3graph.emplace_shared<PriorFactor<Pose3> >(keyAnchor, Pose3(), priorModel);
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initialPose.insert(kAnchorKey, Pose3());
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pose3graph.emplace_shared<PriorFactor<Pose3> >(kAnchorKey, Pose3(), priorModel);
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// Create optimizer
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GaussNewtonParams params;
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bool singleIter = true;
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if(singleIter){
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if (singleIter) {
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params.maxIterations = 1;
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}else{
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std::cout << " \n\n\n\n performing more than 1 GN iterations \n\n\n" <<std::endl;
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} else {
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cout << " \n\n\n\n performing more than 1 GN iterations \n\n\n" << endl;
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params.setVerbosity("TERMINATION");
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}
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GaussNewtonOptimizer optimizer(pose3graph, initialPose, params);
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@ -345,9 +328,9 @@ Values computePoses(NonlinearFactorGraph& pose3graph, Values& initialRot) {
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// put into Values structure
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Values estimate;
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for(const Values::ConstKeyValuePair& key_value: GNresult) {
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for (const auto& key_value : GNresult) {
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Key key = key_value.key;
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if (key != keyAnchor) {
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if (key != kAnchorKey) {
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const Pose3& pose = GNresult.at<Pose3>(key);
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estimate.insert(key, pose);
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}
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@ -356,22 +339,9 @@ Values computePoses(NonlinearFactorGraph& pose3graph, Values& initialRot) {
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}
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/* ************************************************************************* */
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Values initialize(const NonlinearFactorGraph& graph) {
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Values initialize(const NonlinearFactorGraph& graph, const Values& givenGuess,
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bool useGradient) {
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gttic(InitializePose3_initialize);
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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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// Get orientations from relative orientation measurements
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Values valueRot3 = computeOrientationsChordal(pose3Graph);
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// Compute the full poses (1 GN iteration on full poses)
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return computePoses(pose3Graph, valueRot3);
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}
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/* ************************************************************************* */
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Values initialize(const NonlinearFactorGraph& graph, const Values& givenGuess, bool useGradient) {
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Values initialValues;
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// We "extract" the Pose3 subgraph of the original graph: this
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@ -380,27 +350,19 @@ Values initialize(const NonlinearFactorGraph& graph, const Values& givenGuess, b
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// Get orientations from relative orientation measurements
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Values orientations;
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if(useGradient)
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if (useGradient)
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orientations = computeOrientationsGradient(pose3Graph, givenGuess);
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else
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orientations = computeOrientationsChordal(pose3Graph);
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// orientations.print("orientations\n");
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// Compute the full poses (1 GN iteration on full poses)
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return computePoses(pose3Graph, orientations);
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// for(const Values::ConstKeyValuePair& key_value: orientations) {
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// Key key = key_value.key;
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// if (key != keyAnchor) {
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// const Point3& pos = givenGuess.at<Pose3>(key).translation();
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// const Rot3& rot = orientations.at<Rot3>(key);
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// Pose3 initializedPoses = Pose3(rot, pos);
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// initialValues.insert(key, initializedPoses);
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// }
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// }
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// return initialValues;
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}
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} // end of namespace lago
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} // end of namespace gtsam
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/* ************************************************************************* */
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Values 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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@ -20,40 +20,65 @@
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#pragma once
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/geometry/Rot3.h>
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#include <gtsam/inference/graph.h>
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#include <gtsam/linear/GaussianFactorGraph.h>
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#include <gtsam/linear/VectorValues.h>
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#include <gtsam/inference/graph.h>
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#include <gtsam/geometry/Rot3.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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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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typedef std::map<Key, Rot3> KeyRotMap;
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namespace InitializePose3 {
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namespace initialize_pose3 {
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GTSAM_EXPORT GaussianFactorGraph buildLinearOrientationGraph(const NonlinearFactorGraph& g);
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GTSAM_EXPORT GaussianFactorGraph
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buildLinearOrientationGraph(const NonlinearFactorGraph& g);
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GTSAM_EXPORT Values normalizeRelaxedRotations(const VectorValues& relaxedRot3);
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GTSAM_EXPORT Values computeOrientationsChordal(const NonlinearFactorGraph& pose3Graph);
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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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GTSAM_EXPORT Values computeOrientationsGradient(const NonlinearFactorGraph& pose3Graph,
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const Values& givenGuess, size_t maxIter = 10000, const bool setRefFrame = true);
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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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const NonlinearFactorGraph& pose3Graph, const Values& givenGuess,
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size_t maxIter = 10000, const bool setRefFrame = true);
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|
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GTSAM_EXPORT void createSymbolicGraph(KeyVectorMap& adjEdgesMap, KeyRotMap& factorId2RotMap,
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GTSAM_EXPORT 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, const double a, const double b);
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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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GTSAM_EXPORT NonlinearFactorGraph buildPose3graph(const NonlinearFactorGraph& graph);
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/**
|
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* Select the subgraph of betweenFactors and transforms priors into between wrt
|
||||
* a fictitious node
|
||||
*/
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GTSAM_EXPORT NonlinearFactorGraph
|
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buildPose3graph(const NonlinearFactorGraph& graph);
|
||||
|
||||
GTSAM_EXPORT Values computePoses(NonlinearFactorGraph& pose3graph, Values& initialRot);
|
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GTSAM_EXPORT Values computePoses(NonlinearFactorGraph& pose3graph,
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Values& initialRot);
|
||||
|
||||
/**
|
||||
* "extract" the Pose3 subgraph of the original graph, get orientations from
|
||||
* relative orientation measurements (using either gradient or chordal method),
|
||||
* and finish up with 1 GN iteration on full poses.
|
||||
*/
|
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GTSAM_EXPORT Values initialize(const NonlinearFactorGraph& graph,
|
||||
const Values& givenGuess,
|
||||
bool useGradient = false);
|
||||
|
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/// Calls initialize above using Chordal method.
|
||||
GTSAM_EXPORT Values initialize(const NonlinearFactorGraph& graph);
|
||||
|
||||
GTSAM_EXPORT Values initialize(const NonlinearFactorGraph& graph, const Values& givenGuess, bool useGradient = false);
|
||||
|
||||
} // end of namespace lago
|
||||
} // namespace initialize_pose3
|
||||
} // end of namespace gtsam
|
||||
|
|
|
|||
|
|
@ -74,15 +74,15 @@ NonlinearFactorGraph graph() {
|
|||
|
||||
/* *************************************************************************** */
|
||||
TEST( InitializePose3, buildPose3graph ) {
|
||||
NonlinearFactorGraph pose3graph = InitializePose3::buildPose3graph(simple::graph());
|
||||
NonlinearFactorGraph pose3graph = initialize_pose3::buildPose3graph(simple::graph());
|
||||
// pose3graph.print("");
|
||||
}
|
||||
|
||||
/* *************************************************************************** */
|
||||
TEST( InitializePose3, orientations ) {
|
||||
NonlinearFactorGraph pose3Graph = InitializePose3::buildPose3graph(simple::graph());
|
||||
NonlinearFactorGraph pose3Graph = initialize_pose3::buildPose3graph(simple::graph());
|
||||
|
||||
Values initial = InitializePose3::computeOrientationsChordal(pose3Graph);
|
||||
Values initial = initialize_pose3::computeOrientationsChordal(pose3Graph);
|
||||
|
||||
// comparison is up to M_PI, that's why we add some multiples of 2*M_PI
|
||||
EXPECT(assert_equal(simple::R0, initial.at<Rot3>(x0), 1e-6));
|
||||
|
|
@ -93,12 +93,12 @@ TEST( InitializePose3, orientations ) {
|
|||
|
||||
/* *************************************************************************** */
|
||||
TEST( InitializePose3, orientationsGradientSymbolicGraph ) {
|
||||
NonlinearFactorGraph pose3Graph = InitializePose3::buildPose3graph(simple::graph());
|
||||
NonlinearFactorGraph pose3Graph = initialize_pose3::buildPose3graph(simple::graph());
|
||||
|
||||
KeyVectorMap adjEdgesMap;
|
||||
KeyRotMap factorId2RotMap;
|
||||
|
||||
InitializePose3::createSymbolicGraph(adjEdgesMap, factorId2RotMap, pose3Graph);
|
||||
initialize_pose3::createSymbolicGraph(adjEdgesMap, factorId2RotMap, pose3Graph);
|
||||
|
||||
EXPECT_DOUBLES_EQUAL(adjEdgesMap.at(x0)[0], 0, 1e-9);
|
||||
EXPECT_DOUBLES_EQUAL(adjEdgesMap.at(x0)[1], 3, 1e-9);
|
||||
|
|
@ -132,7 +132,7 @@ TEST( InitializePose3, singleGradient ) {
|
|||
double a = 6.010534238540223;
|
||||
double b = 1.0;
|
||||
|
||||
Vector actual = InitializePose3::gradientTron(R1, R2, a, b);
|
||||
Vector actual = initialize_pose3::gradientTron(R1, R2, a, b);
|
||||
Vector expected = Vector3::Zero();
|
||||
expected(2) = 1.962658662803917;
|
||||
|
||||
|
|
@ -142,7 +142,7 @@ TEST( InitializePose3, singleGradient ) {
|
|||
|
||||
/* *************************************************************************** */
|
||||
TEST( InitializePose3, iterationGradient ) {
|
||||
NonlinearFactorGraph pose3Graph = InitializePose3::buildPose3graph(simple::graph());
|
||||
NonlinearFactorGraph pose3Graph = initialize_pose3::buildPose3graph(simple::graph());
|
||||
|
||||
// Wrong initial guess - initialization should fix the rotations
|
||||
Rot3 Rpert = Rot3::Expmap(Vector3(0.01, 0.01, 0.01));
|
||||
|
|
@ -154,7 +154,7 @@ TEST( InitializePose3, iterationGradient ) {
|
|||
|
||||
size_t maxIter = 1; // test gradient at the first iteration
|
||||
bool setRefFrame = false;
|
||||
Values orientations = InitializePose3::computeOrientationsGradient(pose3Graph, givenPoses, maxIter, setRefFrame);
|
||||
Values orientations = initialize_pose3::computeOrientationsGradient(pose3Graph, givenPoses, maxIter, setRefFrame);
|
||||
|
||||
Matrix M0 = (Matrix(3,3) << 0.999435813876064, -0.033571481675497, 0.001004768630281,
|
||||
0.033572116359134, 0.999436104312325, -0.000621610948719,
|
||||
|
|
@ -183,7 +183,7 @@ TEST( InitializePose3, iterationGradient ) {
|
|||
|
||||
/* *************************************************************************** */
|
||||
TEST( InitializePose3, orientationsGradient ) {
|
||||
NonlinearFactorGraph pose3Graph = InitializePose3::buildPose3graph(simple::graph());
|
||||
NonlinearFactorGraph pose3Graph = initialize_pose3::buildPose3graph(simple::graph());
|
||||
|
||||
// Wrong initial guess - initialization should fix the rotations
|
||||
Rot3 Rpert = Rot3::Expmap(Vector3(0.01, 0.01, 0.01));
|
||||
|
|
@ -194,7 +194,7 @@ TEST( InitializePose3, orientationsGradient ) {
|
|||
givenPoses.insert(x3, (simple::pose0).compose( Pose3(Rpert,Point3(0,0,0)) ));
|
||||
// do 10 gradient iterations
|
||||
bool setRefFrame = false;
|
||||
Values orientations = InitializePose3::computeOrientationsGradient(pose3Graph, givenPoses, 10, setRefFrame);
|
||||
Values orientations = initialize_pose3::computeOrientationsGradient(pose3Graph, givenPoses, 10, setRefFrame);
|
||||
|
||||
// const Key keyAnchor = symbol('Z', 9999999);
|
||||
// givenPoses.insert(keyAnchor,simple::pose0);
|
||||
|
|
@ -228,7 +228,7 @@ TEST( InitializePose3, posesWithGivenGuess ) {
|
|||
givenPoses.insert(x2,simple::pose2);
|
||||
givenPoses.insert(x3,simple::pose3);
|
||||
|
||||
Values initial = InitializePose3::initialize(simple::graph(), givenPoses);
|
||||
Values initial = initialize_pose3::initialize(simple::graph(), givenPoses);
|
||||
|
||||
// comparison is up to M_PI, that's why we add some multiples of 2*M_PI
|
||||
EXPECT(assert_equal(givenPoses, initial, 1e-6));
|
||||
|
|
@ -245,7 +245,7 @@ TEST( InitializePose3, initializePoses )
|
|||
noiseModel::Unit::shared_ptr priorModel = noiseModel::Unit::Create(6);
|
||||
inputGraph->add(PriorFactor<Pose3>(0, Pose3(), priorModel));
|
||||
|
||||
Values initial = InitializePose3::initialize(*inputGraph);
|
||||
Values initial = initialize_pose3::initialize(*inputGraph);
|
||||
EXPECT(assert_equal(*expectedValues,initial,0.1)); // TODO(frank): very loose !!
|
||||
}
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue