CMetricMap.h

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/* +------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)            |
   |                          http://www.mrpt.org/                          |
   |                                                                        |
   | Copyright (c) 2005-2018, Individual contributors, see AUTHORS file     |
   | See: http://www.mrpt.org/Authors - All rights reserved.                |
   | Released under BSD License. See details in http://www.mrpt.org/License |
   +------------------------------------------------------------------------+ */
#ifndef CMetricMap_H
#define CMetricMap_H
 
#include <mrpt/serialization/CSerializable.h>
#include <mrpt/tfest/TMatchingPair.h>
#include <mrpt/system/CObservable.h>
#include <mrpt/math/math_frwds.h>
#include <mrpt/math/lightweight_geom_data.h>
#include <mrpt/obs/CObservation.h>
#include <mrpt/opengl/CSetOfObjects.h>
#include <mrpt/maps/CMetricMapEvents.h>
#include <mrpt/maps/TMetricMapInitializer.h>
#include <mrpt/maps/metric_map_types.h>
#include <mrpt/obs/obs_frwds.h>
#include <deque>
 
namespace mrpt
{
namespace maps
{
/** Declares a virtual base class for all metric maps storage classes.
 *  In this class virtual methods are provided to allow the insertion
 *  of any type of "CObservation" objects into the metric map, thus
 *  updating the map (doesn't matter if it is a 2D/3D grid, a point map, etc.).
 *
 *  Observations don't include any information about the
 *  robot pose, just the raw observation and information about
 *  the sensor pose relative to the robot mobile base coordinates origin.
 *
 *  Note that all metric maps implement this mrpt::system::CObservable
 *interface,
 *   emitting the following events:
 *        - mrpt::obs::mrptEventMetricMapClear: Upon call of the ::clear() method.
 *    - mrpt::obs::mrptEventMetricMapInsert: Upon insertion of an observation
 *that effectively modifies the map (e.g. inserting an image into a grid map
 *will NOT raise an event, inserting a laser scan will).
 *
 * To check what observations are supported by each metric map, see: \ref
 *maps_observations
 *
 * \note All derived class must implement a static class factory
 *`<metric_map_class>::MapDefinition()` that builds a default
 *TMetricMapInitializer [New in MRPT 1.3.0]
 *
 * \sa CObservation, CSensoryFrame, CMultiMetricMap
 * \ingroup mrpt_obs_grp
 */
class CMetricMap : public mrpt::serialization::CSerializable,
                                   public mrpt::system::CObservable
{
        DEFINE_VIRTUAL_SERIALIZABLE(CMetricMap)
 
   private:
        /** Internal method called by clear() */
        virtual void internal_clear() = 0;
 
        /** Internal method called by insertObservation() */
        virtual bool internal_insertObservation(
                const mrpt::obs::CObservation* obs,
                const mrpt::poses::CPose3D* robotPose = NULL) = 0;
 
        /** Internal method called by computeObservationLikelihood() */
        virtual double internal_computeObservationLikelihood(
                const mrpt::obs::CObservation* obs,
                const mrpt::poses::CPose3D& takenFrom) = 0;
        /** Internal method called by canComputeObservationLikelihood() */
        virtual bool internal_canComputeObservationLikelihood(
                const mrpt::obs::CObservation* obs) const
        {
                MRPT_UNUSED_PARAM(obs);
                return true;  // Unless implemented otherwise, assume we can always
                // compute the likelihood.
        }
 
        /** Hook for each time a "internal_insertObservation" returns "true"
          * This is called automatically from insertObservation() when
         * internal_insertObservation returns true. */
        virtual void OnPostSuccesfulInsertObs(const mrpt::obs::CObservation*)
        { /* Default: do nothing */}
 
   public:
        /** Erase all the contents of the map */
        void clear();
 
        /** Returns true if the map is empty/no observation has been inserted.
          */
        virtual bool isEmpty() const = 0;
 
        /** Load the map contents from a CSimpleMap object, erasing all previous
         * content of the map. This is done invoking `insertObservation()` for each
         * observation at the mean 3D robot pose of each pose-observations pair in
         * the CSimpleMap object.
         *
         * \sa insertObservation, CSimpleMap
         * \exception std::exception Some internal steps in invoked methods can
         * raise exceptions on invalid parameters, etc...
         */
        void loadFromProbabilisticPosesAndObservations(
                const mrpt::maps::CSimpleMap& Map);
 
        ///! \overload
        inline void loadFromSimpleMap(const mrpt::maps::CSimpleMap& Map)
        {
                loadFromProbabilisticPosesAndObservations(Map);
        }
 
        /** Insert the observation information into this map. This method must be
         * implemented
         *    in derived classes. See: \ref maps_observations
         * \param obs The observation
         * \param robotPose The 3D pose of the robot mobile base in the map
         * reference system, or NULL (default) if you want to use the origin.
         *
         * \sa CObservation::insertObservationInto
         */
        bool insertObservation(
                const mrpt::obs::CObservation* obs,
                const mrpt::poses::CPose3D* robotPose = NULL);
 
        /** A wrapper for smart pointers, just calls the non-smart pointer version.
         * See: \ref maps_observations  */
        bool insertObservationPtr(
                const mrpt::obs::CObservation::Ptr& obs,
                const mrpt::poses::CPose3D* robotPose = NULL);
 
        /** Computes the log-likelihood of a given observation given an arbitrary
         * robot 3D pose.  See: \ref maps_observations
         *
         * \param takenFrom The robot's pose the observation is supposed to be taken
         * from.
         * \param obs The observation.
         * \return This method returns a log-likelihood.
         *
         * \sa Used in particle filter algorithms, see: CMultiMetricMapPDF::update
         */
        double computeObservationLikelihood(
                const mrpt::obs::CObservation* obs,
                const mrpt::poses::CPose3D& takenFrom);
 
        /** \overload */
        double computeObservationLikelihood(
                const mrpt::obs::CObservation* obs,
                const mrpt::poses::CPose2D& takenFrom);
 
        /** Returns true if this map is able to compute a sensible likelihood
         * function for this observation (i.e. an occupancy grid map cannot with an
         * image).  See: \ref maps_observations
         * \param obs The observation.
         * \sa computeObservationLikelihood,
         * genericMapParams.enableObservationLikelihood
         */
        virtual bool canComputeObservationLikelihood(
                const mrpt::obs::CObservation* obs) const;
 
        /** \overload */
        bool canComputeObservationLikelihood(
                const mrpt::obs::CObservation::Ptr& obs) const;
 
        /** Returns the sum of the log-likelihoods of each individual observation
         * within a mrpt::obs::CSensoryFrame.  See: \ref maps_observations
         *
         * \param takenFrom The robot's pose the observation is supposed to be taken
         * from.
         * \param sf The set of observations in a CSensoryFrame.
         * \return This method returns a log-likelihood.
         * \sa canComputeObservationsLikelihood
         */
        double computeObservationsLikelihood(
                const mrpt::obs::CSensoryFrame& sf,
                const mrpt::poses::CPose2D& takenFrom);
 
        /** Returns true if this map is able to compute a sensible likelihood
         * function for this observation (i.e. an occupancy grid map cannot with an
         * image).  See: \ref maps_observations
         * \param sf The observations.
         * \sa canComputeObservationLikelihood
         */
        bool canComputeObservationsLikelihood(
                const mrpt::obs::CSensoryFrame& sf) const;
 
        /** Constructor */
        CMetricMap();
 
        /** Computes the matching between this and another 2D point map, which
         *includes finding:
         *   - The set of points pairs in each map
         *   - The mean squared distance between corresponding pairs.
         *
         *   The algorithm is:
         *              - For each point in "otherMap":
         *                      - Transform the point according to otherMapPose
         *                      - Search with a KD-TREE the closest correspondences in "this"
         *map.
         *                      - Add to the set of candidate matchings, if it passes all the
         *thresholds in params.
         *
         *   This method is the most time critical one into ICP-like algorithms.
         *
         * \param  otherMap        [IN] The other map to compute the matching with.
         * \param  otherMapPose    [IN] The pose of the other map as seen from
         *"this".
         * \param  params          [IN] Parameters for the determination of
         *pairings.
         * \param  correspondences [OUT] The detected matchings pairs.
         * \param  extraResults    [OUT] Other results.
         * \sa compute3DMatchingRatio
         */
        virtual void determineMatching2D(
                const mrpt::maps::CMetricMap* otherMap,
                const mrpt::poses::CPose2D& otherMapPose,
                mrpt::tfest::TMatchingPairList& correspondences,
                const TMatchingParams& params,
                TMatchingExtraResults& extraResults) const;
 
        /** Computes the matchings between this and another 3D points map - method
         *used in 3D-ICP.
         *  This method finds the set of point pairs in each map.
         *
         *  The method is the most time critical one into ICP-like algorithms.
         *
         *  The algorithm is:
         *              - For each point in "otherMap":
         *                      - Transform the point according to otherMapPose
         *                      - Search with a KD-TREE the closest correspondences in "this"
         *map.
         *                      - Add to the set of candidate matchings, if it passes all the
         *thresholds in params.
         *
         * \param  otherMap        [IN] The other map to compute the matching with.
         * \param  otherMapPose    [IN] The pose of the other map as seen from
         *"this".
         * \param  params          [IN] Parameters for the determination of
         *pairings.
         * \param  correspondences [OUT] The detected matchings pairs.
         * \param  extraResults    [OUT] Other results.
         * \sa compute3DMatchingRatio
         */
        virtual void determineMatching3D(
                const mrpt::maps::CMetricMap* otherMap,
                const mrpt::poses::CPose3D& otherMapPose,
                mrpt::tfest::TMatchingPairList& correspondences,
                const TMatchingParams& params,
                TMatchingExtraResults& extraResults) const;
 
        /** Computes the ratio in [0,1] of correspondences between "this" and the
         * "otherMap" map, whose 6D pose relative to "this" is "otherMapPose"
         *   In the case of a multi-metric map, this returns the average between the
         * maps. This method always return 0 for grid maps.
         * \param  otherMap      [IN] The other map to compute the matching with.
         * \param  otherMapPose  [IN] The 6D pose of the other map as seen from
         * "this".
         * \param  params        [IN] Matching parameters
         * \return The matching ratio [0,1]
         * \sa determineMatching2D
         */
        virtual float compute3DMatchingRatio(
                const mrpt::maps::CMetricMap* otherMap,
                const mrpt::poses::CPose3D& otherMapPose,
                const TMatchingRatioParams& params) const;
 
        /** This virtual method saves the map to a file "filNamePrefix"+<
         * some_file_extension >, as an image or in any other applicable way (Notice
         * that other methods to save the map may be implemented in classes
         * implementing this virtual interface). */
        virtual void saveMetricMapRepresentationToFile(
                const std::string& filNamePrefix) const = 0;
 
        /** Returns a 3D object representing the map.
          * \sa genericMapParams, TMapGenericParams::enableSaveAs3DObject */
        virtual void getAs3DObject(
                mrpt::opengl::CSetOfObjects::Ptr& outObj) const = 0;
 
        /** Common params to all maps */
        TMapGenericParams genericMapParams;
 
        /** This method is called at the end of each "prediction-update-map
         * insertion" cycle within
         * "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".
          *  This method should normally do nothing, but in some cases can be used
         * to free auxiliary cached variables.
          */
        virtual void auxParticleFilterCleanUp()
        { /* Default implementation: do nothing. */}
 
        /** Returns the square distance from the 2D point (x0,y0) to the closest
         * correspondence in the map. */
        virtual float squareDistanceToClosestCorrespondence(
                float x0, float y0) const;
 
        /** If the map is a simple points map or it's a multi-metric map that
         * contains EXACTLY one simple points map, return it.
          * Otherwise, return NULL
          */
        virtual const mrpt::maps::CSimplePointsMap* getAsSimplePointsMap() const
        {
                return NULL;
        }
        virtual mrpt::maps::CSimplePointsMap* getAsSimplePointsMap()
        {
                return NULL;
        }
 
};  // End of class def.
 
/** A list of metric maps (used in the mrpt::poses::CPosePDFParticles class):
  */
using TMetricMapList = std::deque<CMetricMap*>;
 
}  // End of namespace
}  // End of namespace
 
#endif