CMonteCarloLocalization2D.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 CMonteCarloLocalization2D_H
#define CMonteCarloLocalization2D_H
 
#include <mrpt/poses/CPosePDFParticles.h>
#include <mrpt/slam/PF_implementations_data.h>
#include <mrpt/slam/TMonteCarloLocalizationParams.h>
#include <mrpt/obs/obs_frwds.h>
 
#include <mrpt/slam/PF_aux_structs.h>
 
namespace mrpt
{
namespace maps
{
class COccupancyGridMap2D;
}
 
/** \ingroup mrpt_slam_grp */
namespace slam
{
/** Declares a class that represents a Probability Density Function (PDF) over a
 * 2D pose (x,y,phi), using a set of weighted samples.
 *
 *  This class also implements particle filtering for robot localization. See
 * the MRPT
 *   application "app/pf-localization" for an example of usage.
 *
 * \sa CMonteCarloLocalization3D, CPose2D, CPosePDF, CPoseGaussianPDF,
 * \ingroup mrpt_slam_grp
 */
class CMonteCarloLocalization2D
        : public PF_implementation<
                  mrpt::poses::CPose2D, mrpt::poses::CPosePDFParticles>
{
   public:
        using CParticleDataContent =
                mrpt::poses::CPosePDFParticles::CParticleDataContent;
        using CParticleList = mrpt::poses::CPosePDFParticles::CParticleList;
 
        mrpt::poses::CPosePDFParticles m_poseParticles;
 
        /** MCL parameters */
        TMonteCarloLocalizationParams options;
 
        /** Constructor
         * \param M The number of m_particles.
         */
        CMonteCarloLocalization2D(size_t M = 1);
 
        /** Destructor */
        virtual ~CMonteCarloLocalization2D();
 
        /** Reset the PDF to an uniformly distributed one, but only in the
         * free-space
         *   of a given 2D occupancy-grid-map. Orientation is randomly generated in
         * the whole 2*PI range.
         * \param theMap The occupancy grid map
         * \param freeCellsThreshold The minimum free-probability to consider a
         * cell as empty (default is 0.7)
         * \param particlesCount If set to -1 the number of m_particles remains
         * unchanged.
         * \param x_min The limits of the area to look for free cells.
         * \param x_max The limits of the area to look for free cells.
         * \param y_min The limits of the area to look for free cells.
         * \param y_max The limits of the area to look for free cells.
         * \param phi_min The limits of the area to look for free cells.
         * \param phi_max The limits of the area to look for free cells.
         *  \sa resetDeterm32inistic
         * \exception std::exception On any error (no free cell found in map,
         * map=nullptr, etc...)
         */
        void resetUniformFreeSpace(
                mrpt::maps::COccupancyGridMap2D* theMap,
                const double freeCellsThreshold = 0.7, const int particlesCount = -1,
                const double x_min = -1e10f, const double x_max = 1e10f,
                const double y_min = -1e10f, const double y_max = 1e10f,
                const double phi_min = -M_PI, const double phi_max = M_PI);
 
        /** Update the m_particles, predicting the posterior of robot pose and map
         * after a movement command.
         *  This method has additional configuration parameters in "options".
         *  Performs the update stage of the RBPF, using the sensed CSensoryFrame:
         *
         *   \param action This is a pointer to CActionCollection, containing the
         * pose change the robot has been commanded.
         *   \param observation This must be a pointer to a CSensoryFrame object,
         * with robot sensed observations.
         *
         * \sa options
         */
        template <class T>
        void prediction_and_update(
                const mrpt::obs::CActionCollection* actions,
                const mrpt::obs::CSensoryFrame* observation,
                const bayes::CParticleFilter::TParticleFilterOptions& PF_options)
        {
                MRPT_START
 
                if (observation)
                {  // A map MUST be supplied!
                        ASSERT_(options.metricMap || options.metricMaps.size() > 0)
                        if (!options.metricMap)
                                ASSERT_(
                                        options.metricMaps.size() ==
                                        m_poseParticles.m_particles.size())
                }
 
                T::template PF_SLAM_implementation<
                        mrpt::poses::CPose2D, CMonteCarloLocalization2D,
                        mrpt::slam::detail::TPoseBin2D>(
                        actions, observation, PF_options, options.KLD_params, *this);
 
                MRPT_END
        }
        // protected:
        /** \name Virtual methods that the PF_implementations assume exist.
                @{ */
        /** Return the robot pose for the i'th particle. is_valid is
         * always true in this class. */
        mrpt::math::TPose3D getLastPose(
                const size_t i, bool& is_valid_pose) const override;
 
        void PF_SLAM_implementation_custom_update_particle_with_new_pose(
                CParticleDataContent* particleData,
                const mrpt::math::TPose3D& newPose) const override;
 
        // We'll redefine this one:
        void PF_SLAM_implementation_replaceByNewParticleSet(
                CParticleList& old_particles,
                const std::vector<mrpt::math::TPose3D>& newParticles,
                const std::vector<double>& newParticlesWeight,
                const std::vector<size_t>& newParticlesDerivedFromIdx) const override;
 
        /** Evaluate the observation likelihood for one particle at a given location
         */
        double PF_SLAM_computeObservationLikelihoodForParticle(
                const mrpt::bayes::CParticleFilter::TParticleFilterOptions& PF_options,
                const size_t particleIndexForMap,
                const mrpt::obs::CSensoryFrame& observation,
                const mrpt::poses::CPose3D& x) const override;
        /** @} */
 
        void executeOn(
                mrpt::bayes::CParticleFilter& pf,
                const mrpt::obs::CActionCollection* action,
                const mrpt::obs::CSensoryFrame* observation,
                mrpt::bayes::CParticleFilter::TParticleFilterStats* stats,
                mrpt::bayes::CParticleFilter::TParticleFilterAlgorithm PF_algorithm);
 
};  // End of class def.
 
}  // namespace slam
}  // namespace mrpt
 
#endif