100 lines
2.8 KiB
C++
100 lines
2.8 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 PriorFactor.h
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* @author Frank Dellaert
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**/
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#pragma once
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#include <gtsam/nonlinear/NonlinearFactor.h>
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#include <gtsam/base/Testable.h>
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namespace gtsam {
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/**
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* A class for a soft prior on any Lie type
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* It takes two template parameters:
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* Key (typically TypedSymbol) is used to look up T's in a Values
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* Values where the T's are stored, typically LieValues<Key> or a TupleValues<...>
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* The Key type is not arbitrary: we need to cast to a Symbol at linearize, so
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* a simple type like int will not work
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*/
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template<class VALUES, class KEY>
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class PriorFactor: public NonlinearFactor1<VALUES, KEY> {
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public:
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typedef typename KEY::Value T;
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private:
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typedef NonlinearFactor1<VALUES, KEY> Base;
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T prior_; /** The measurement */
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/** concept check by type */
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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<PriorFactor> shared_ptr;
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/** default constructor - only use for serialization */
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PriorFactor() {}
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virtual ~PriorFactor() {}
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/** Constructor */
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PriorFactor(const KEY& key, const T& prior,
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const SharedNoiseModel& model) :
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Base(model, key), prior_(prior) {
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}
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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 {
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std::cout << s << "PriorFactor(" << (std::string) this->key_ << ")\n";
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prior_.print(" prior");
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this->noiseModel_->print(" noise model");
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}
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/** equals */
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virtual bool equals(const NonlinearFactor<VALUES>& expected, double tol=1e-9) const {
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const PriorFactor<VALUES, KEY> *e = dynamic_cast<const PriorFactor<
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VALUES, KEY>*> (&expected);
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return e != NULL && Base::equals(*e, tol) && this->prior_.equals(e->prior_, tol);
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}
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/** implement functions needed to derive from Factor */
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/** vector of errors */
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Vector evaluateError(const T& p, boost::optional<Matrix&> H = boost::none) const {
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if (H) (*H) = eye(p.dim());
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// manifold equivalent of h(x)-z -> log(z,h(x))
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return prior_.localCoordinates(p);
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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("NonlinearFactor1",
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boost::serialization::base_object<Base>(*this));
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ar & BOOST_SERIALIZATION_NVP(prior_);
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}
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};
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} /// namespace gtsam
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