maps/CMetricMap.h

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/* +---------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)               |
   |                          http://www.mrpt.org/                             |
   |                                                                           |
   | Copyright (c) 2005-2017, 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/utils/CSerializable.h>
#include <mrpt/utils/TMatchingPair.h>
#include <mrpt/utils/CObservable.h>
#include <mrpt/math/math_frwds.h>
#include <mrpt/math/lightweight_geom_data.h>
#include <mrpt/opengl/opengl_frwds.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 <mrpt/obs/link_pragmas.h>
#include <deque>
 
namespace mrpt
{
        namespace maps
        {
                DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE_LINKAGE( CMetricMap, mrpt::utils::CSerializable, OBS_IMPEXP )
 
                /** 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::utils::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 OBS_IMPEXP CMetricMap :
                        public mrpt::utils::CSerializable,
                        public mrpt::utils::CObservable
                {
                        // This must be added to any CSerializable derived class:
                        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 automaticed invoking "insertObservation" for each observation at the mean 3D robot pose as
                         *   given by the "poses::CPosePDF" 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 );
 
                        /** Load the map contents from a CSimpleMap object, erasing all previous content of the map.
                         *  This is automaticed invoking "insertObservation" for each observation at the mean 3D robot pose as
                         *   given by the "poses::CPosePDF" in the CSimpleMap object.
                         *
                         * \sa insertObservation, CSimpleMap
                         * \exception std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc...
                         */
                        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::CObservationPtr &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::CObservationPtr &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::utils::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::utils::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::CSetOfObjectsPtr     &outObj ) const = 0;
 
                        TMapGenericParams genericMapParams; //!< Common params to all maps
 
                        /** 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.
                DEFINE_SERIALIZABLE_POST_CUSTOM_BASE_LINKAGE( CMetricMap, mrpt::utils::CSerializable, OBS_IMPEXP )
 
                /** A list of metric maps (used in the mrpt::poses::CPosePDFParticles class):
                  */
                typedef std::deque<CMetricMap*> TMetricMapList;
 
        } // End of namespace
} // End of namespace
 
#endif