234 lines
7.3 KiB
C++
234 lines
7.3 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file TransformBtwRobotsUnaryFactor.h
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* @brief Unary factor for determining transformation between given trajectories of two robots
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* @author Vadim Indelman
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**/
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#pragma once
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#include <gtsam/slam/BetweenFactor.h>
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#include <gtsam/nonlinear/NonlinearFactor.h>
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#include <gtsam/linear/GaussianFactor.h>
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#include <gtsam/base/Testable.h>
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#include <gtsam/base/Lie.h>
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#include <ostream>
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namespace gtsam {
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/**
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* A class for a measurement predicted by "between(config[key1],config[key2])"
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* @tparam VALUE the Value type
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* @addtogroup SLAM
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*/
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template<class VALUE>
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class TransformBtwRobotsUnaryFactor: public NonlinearFactor { // TODO why not NoiseModelFactor1 ?
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public:
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typedef VALUE T;
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private:
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typedef TransformBtwRobotsUnaryFactor<VALUE> This;
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typedef gtsam::NonlinearFactor Base;
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gtsam::Key key_;
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VALUE measured_; /** The measurement */
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gtsam::Values valA_; // given values for robot A map\trajectory
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gtsam::Values valB_; // given values for robot B map\trajectory
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gtsam::Key keyA_; // key of robot A to which the measurement refers
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gtsam::Key keyB_; // key of robot B to which the measurement refers
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SharedGaussian model_;
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/** concept check by type */
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GTSAM_CONCEPT_LIE_TYPE(T)
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GTSAM_CONCEPT_TESTABLE_TYPE(T)
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public:
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// shorthand for a smart pointer to a factor
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typedef typename boost::shared_ptr<TransformBtwRobotsUnaryFactor> shared_ptr;
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/** default constructor - only use for serialization */
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TransformBtwRobotsUnaryFactor() {}
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/** Constructor */
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TransformBtwRobotsUnaryFactor(Key key, const VALUE& measured, Key keyA, Key keyB,
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const gtsam::Values& valA, const gtsam::Values& valB,
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const SharedGaussian& model) :
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Base(cref_list_of<1>(key)), key_(key), measured_(measured), keyA_(keyA), keyB_(keyB),
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model_(model){
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setValAValB(valA, valB);
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}
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virtual ~TransformBtwRobotsUnaryFactor() {}
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/** Clone */
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virtual gtsam::NonlinearFactor::shared_ptr clone() const { return boost::make_shared<This>(*this); }
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/** implement functions needed for Testable */
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/** print */
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virtual void print(const std::string& s, const KeyFormatter& keyFormatter = DefaultKeyFormatter) const {
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std::cout << s << "TransformBtwRobotsUnaryFactor("
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<< keyFormatter(key_) << ")\n";
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std::cout << "MR between factor keys: "
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<< keyFormatter(keyA_) << ","
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<< keyFormatter(keyB_) << "\n";
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measured_.print(" measured: ");
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model_->print(" noise model: ");
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// Base::print(s, keyFormatter);
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}
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/** equals */
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virtual bool equals(const NonlinearFactor& f, double tol=1e-9) const {
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const This *t = dynamic_cast<const This*> (&f);
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if(t && Base::equals(f))
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return key_ == t->key_ && measured_.equals(t->measured_);
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else
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return false;
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}
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/** implement functions needed to derive from Factor */
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/* ************************************************************************* */
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void setValAValB(const gtsam::Values& valA, const gtsam::Values& valB){
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if ( (!valA.exists(keyA_)) && (!valB.exists(keyA_)) && (!valA.exists(keyB_)) && (!valB.exists(keyB_)) )
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throw("something is wrong!");
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// TODO: make sure the two keys belong to different robots
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if (valA.exists(keyA_)){
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valA_ = valA;
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valB_ = valB;
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}
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else {
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valA_ = valB;
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valB_ = valA;
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}
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}
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/* ************************************************************************* */
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virtual double error(const gtsam::Values& x) const {
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return whitenedError(x).squaredNorm();
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}
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/* ************************************************************************* */
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/**
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* Linearize a non-linearFactorN to get a gtsam::GaussianFactor,
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* \f$ Ax-b \approx h(x+\delta x)-z = h(x) + A \delta x - z \f$
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* Hence \f$ b = z - h(x) = - \mathtt{error\_vector}(x) \f$
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*/
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/* This version of linearize recalculates the noise model each time */
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virtual boost::shared_ptr<gtsam::GaussianFactor> linearize(const gtsam::Values& x) const {
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// Only linearize if the factor is active
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if (!this->active(x))
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return boost::shared_ptr<gtsam::JacobianFactor>();
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//std::cout<<"About to linearize"<<std::endl;
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gtsam::Matrix A1;
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std::vector<gtsam::Matrix> A(this->size());
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gtsam::Vector b = -whitenedError(x, A);
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A1 = A[0];
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return gtsam::GaussianFactor::shared_ptr(
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new gtsam::JacobianFactor(key_, A1, b, gtsam::noiseModel::Unit::Create(b.size())));
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}
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/* ************************************************************************* */
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gtsam::Vector whitenedError(const gtsam::Values& x,
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boost::optional<std::vector<gtsam::Matrix>&> H = boost::none) const {
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T orgA_T_currA = valA_.at<T>(keyA_);
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T orgB_T_currB = valB_.at<T>(keyB_);
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T orgA_T_orgB = x.at<T>(key_);
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T currA_T_currB_pred;
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if (H) {
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Matrix H_compose, H_between1;
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T orgA_T_currB = orgA_T_orgB.compose(orgB_T_currB, H_compose, boost::none);
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currA_T_currB_pred = orgA_T_currA.between(orgA_T_currB, boost::none, H_between1);
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(*H)[0] = H_compose * H_between1;
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}
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else {
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T orgA_T_currB = orgA_T_orgB.compose(orgB_T_currB);
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currA_T_currB_pred = orgA_T_currA.between(orgA_T_currB);
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}
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const T& currA_T_currB_msr = measured_;
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Vector error = currA_T_currB_msr.localCoordinates(currA_T_currB_pred);
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if (H)
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model_->WhitenSystem(*H, error);
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else
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model_->whitenInPlace(error);
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return error;
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}
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/* ************************************************************************* */
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gtsam::Vector unwhitenedError(const gtsam::Values& x) const {
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T orgA_T_currA = valA_.at<T>(keyA_);
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T orgB_T_currB = valB_.at<T>(keyB_);
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T orgA_T_orgB = x.at<T>(key_);
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T orgA_T_currB = orgA_T_orgB.compose(orgB_T_currB);
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T currA_T_currB_pred = orgA_T_currA.between(orgA_T_currB);
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T currA_T_currB_msr = measured_;
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return currA_T_currB_msr.localCoordinates(currA_T_currB_pred);
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}
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/* ************************************************************************* */
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/** number of variables attached to this factor */
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std::size_t size() const {
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return 1;
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}
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virtual size_t dim() const {
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return model_->R().rows() + model_->R().cols();
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}
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private:
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/** Serialization function */
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friend class boost::serialization::access;
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template<class ARCHIVE>
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void serialize(ARCHIVE & ar, const unsigned int /*version*/) {
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ar & boost::serialization::make_nvp("NonlinearFactor",
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boost::serialization::base_object<Base>(*this));
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//ar & BOOST_SERIALIZATION_NVP(measured_);
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}
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}; // \class TransformBtwRobotsUnaryFactor
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/// traits
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template<class VALUE>
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struct traits<TransformBtwRobotsUnaryFactor<VALUE> > :
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public Testable<TransformBtwRobotsUnaryFactor<VALUE> > {
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};
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} /// namespace gtsam
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