CMetricMapBuilderRBPF.h

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          https://www.mrpt.org/                         |
   |                                                                        |
   | Copyright (c) 2005-2019, Individual contributors, see AUTHORS file     |
   | See: https://www.mrpt.org/Authors - All rights reserved.               |
   | Released under BSD License. See: https://www.mrpt.org/License          |
   +------------------------------------------------------------------------+ */
#pragma once

#include <mrpt/bayes/CParticleFilter.h>
#include <mrpt/bayes/CParticleFilterCapable.h>
#include <mrpt/config/CLoadableOptions.h>
#include <mrpt/core/safe_pointers.h>
#include <mrpt/img/CCanvas.h>
#include <mrpt/maps/CMultiMetricMap.h>
#include <mrpt/maps/CMultiMetricMapPDF.h>
#include <mrpt/slam/CMetricMapBuilder.h>

namespace mrpt::slam
{
/** This class implements a Rao-Blackwelized Particle Filter (RBPF) approach to
 * map building (SLAM).
 *   Internally, the list of particles, each containing a hypothesis for the
 * robot path plus its associated
 *    metric map, is stored in an object of class CMultiMetricMapPDF.
 *
 *  This class processes robot actions and observations sequentially (through
 * the method CMetricMapBuilderRBPF::processActionObservation)
 *   and exploits the generic design of metric map classes in MRPT to deal with
 * any number and combination of maps simultaneously: the likelihood
 *   of observations is the product of the likelihood in the different maps,
 * etc.
 *
 *   A number of particle filter methods are implemented as well, by selecting
 * the appropriate values in TConstructionOptions::PF_options.
 *   Not all the PF algorithms are implemented for all kinds of maps.
 *
 *  For an example of usage, check the application "rbpf-slam", in
 * "apps/RBPF-SLAM". See also the <a
 * href="http://www.mrpt.org/Application:RBPF-SLAM" >wiki page</a>.
 *
 *  \note Since MRPT 0.7.2, the new variables
 * "localizeLinDistance,localizeAngDistance" are introduced to provide a way to
 * update the robot pose at a different rate than the map is updated.
 *  \note Since MRPT 0.7.1 the semantics of the parameters
 * "insertionLinDistance" and "insertionAngDistance" changes: the entire RBFP is
 * now NOT updated unless odometry increments surpass the threshold (previously,
 * only the map was NOT updated). This is done to gain efficiency.
 *  \note Since MRPT 0.6.2 this class implements full 6D SLAM. Previous versions
 * worked in 2D + heading only.
 *
 * \sa CMetricMap   \ingroup metric_slam_grp
 */
class CMetricMapBuilderRBPF : public mrpt::slam::CMetricMapBuilder
{
   public:
    /** The map PDF: It includes a path and associated map for each particle. */
    mrpt::maps::CMultiMetricMapPDF mapPDF;

   protected:
    /** The configuration of the particle filter */
    bayes::CParticleFilter::TParticleFilterOptions m_PF_options;

    /** Distances (linear and angular) for inserting a new observation into the
     * map. */
    float insertionLinDistance, insertionAngDistance;

    /** Distances (linear and angular) for updating the robot pose estimate (and
     * particles weighs, if applicable). */
    float localizeLinDistance, localizeAngDistance;

    /** Traveled distance since last localization update */
    mrpt::poses::CPose3DPDFGaussian odoIncrementSinceLastLocalization;
    /** Traveled distance since last map update */
    mrpt::poses::CPose3D odoIncrementSinceLastMapUpdate;

   public:
    /** Options for building a CMetricMapBuilderRBPF object, passed to the
     * constructor.
     */
    struct TConstructionOptions : public mrpt::config::CLoadableOptions
    {
       public:
        /** Constructor */
        TConstructionOptions();
        void loadFromConfigFile(
            const mrpt::config::CConfigFileBase& source,
            const std::string& section) override;  // See base docs
        void dumpToTextStream(
            std::ostream& out) const override;  // See base docs

        float insertionLinDistance{1.0f};
        float insertionAngDistance;

        float localizeLinDistance{0.4f};
        float localizeAngDistance;

        bayes::CParticleFilter::TParticleFilterOptions PF_options;

        mrpt::maps::TSetOfMetricMapInitializers mapsInitializers;
        mrpt::maps::CMultiMetricMapPDF::TPredictionParams predictionOptions;
        mrpt::system::VerbosityLevel verbosity_level{mrpt::system::LVL_INFO};
    };

    /** Constructor. */
    CMetricMapBuilderRBPF(const TConstructionOptions& initializationOptions);

    /** This second constructor is created for the situation where a class
member needs to be
of type CMetricMapBuilderRBPF  */
    CMetricMapBuilderRBPF();

    /** Copy Operator. */
    CMetricMapBuilderRBPF& operator=(const CMetricMapBuilderRBPF& src);

    /** Destructor. */
    ~CMetricMapBuilderRBPF() override;

    /** Initialize the method, starting with a known location PDF "x0"(if
     * supplied, set to nullptr to left unmodified) and a given fixed, past map.
     */
    void initialize(
        const mrpt::maps::CSimpleMap& initialMap = mrpt::maps::CSimpleMap(),
        const mrpt::poses::CPosePDF* x0 = nullptr) override;

    /** Clear all elements of the maps.
     */
    void clear();

    /** Returns a copy of the current best pose estimation as a pose PDF.
     */
    mrpt::poses::CPose3DPDF::Ptr getCurrentPoseEstimation() const override;

    /** Returns the current most-likely path estimation (the path associated to
     * the most likely particle).
     */
    void getCurrentMostLikelyPath(
        std::deque<mrpt::math::TPose3D>& outPath) const;

    /** Appends a new action and observations to update this map: See the
     *description of the class at the top of this page to see a more complete
     *description.
     *  \param action The incremental 2D pose change in the robot pose. This
     *value is deterministic.
     *  \param observations The set of observations that robot senses at the new
     *pose.
     *  Statistics will be saved to statsLastIteration
     */
    void processActionObservation(
        mrpt::obs::CActionCollection& action,
        mrpt::obs::CSensoryFrame& observations) override;

    /** Fills "out_map" with the set of "poses"-"sensory-frames", thus the so
     * far built map.
     */
    void getCurrentlyBuiltMap(mrpt::maps::CSimpleMap& out_map) const override;

    /** Returns the map built so far. NOTE that for efficiency a pointer to the
     * internal object is passed, DO NOT delete nor modify the object in any
     * way, if desired, make a copy of ir with "clone()".
     */
    const mrpt::maps::CMultiMetricMap* getCurrentlyBuiltMetricMap()
        const override;

    /** Returns just how many sensory-frames are stored in the currently build
     * map.
     */
    unsigned int getCurrentlyBuiltMapSize() override;

    /** A useful method for debugging: the current map (and/or poses) estimation
     * is dumped to an image file.
     * \param file The output file name
     * \param formatEMF_BMP Output format = true:EMF, false:BMP
     */
    void saveCurrentEstimationToImage(
        const std::string& file, bool formatEMF_BMP = true) override;

    /** A useful method for debugging: draws the current map and path hypotheses
     * to a CCanvas  */
    void drawCurrentEstimationToImage(mrpt::img::CCanvas* img);

    /** A logging utility: saves the current path estimation for each particle
     * in a text file (a row per particle, each 3-column-entry is a set
     * [x,y,phi], respectively).
     */
    void saveCurrentPathEstimationToTextFile(const std::string& fil);

    double getCurrentJointEntropy();

    /** This structure will hold stats after each execution of
     * processActionObservation
     */
    struct TStats
    {
        TStats() = default;
        /** Whether the SF has been inserted in the metric maps. */
        bool observationsInserted{false};
    };

    /** This structure will hold stats after each execution of
     * processActionObservation */
    TStats m_statsLastIteration;

};  // End of class def.

}  // namespace mrpt::slam