CPosePDFParticles.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 CPosePDFParticles_H
#define CPosePDFParticles_H

#include <mrpt/poses/CPosePDF.h>
#include <mrpt/poses/CPoseRandomSampler.h>
#include <mrpt/bayes/CParticleFilterCapable.h>
#include <mrpt/bayes/CParticleFilterData.h>

namespace mrpt
{
        namespace poses
        {
                // This must be added to any CSerializable derived class:
                DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE( CPosePDFParticles , CPosePDF )

                /** 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 is also the base for the implementation of Monte-Carlo Localization (MCL), in mrpt::slam::CMonteCarloLocalization2D.
                 *
                 *  See the application "app/pf-localization" for an example of usage.
                 *
                 * \sa CPose2D, CPosePDF, CPoseGaussianPDF, CParticleFilterCapable
                 * \ingroup poses_pdf_grp
                 */
                class BASE_IMPEXP CPosePDFParticles :
                        public CPosePDF,
                        public mrpt::bayes::CParticleFilterData<CPose2D>,
                        public mrpt::bayes::CParticleFilterDataImpl<CPosePDFParticles,mrpt::bayes::CParticleFilterData<CPose2D>::CParticleList>
                {
                        // This must be added to any CSerializable derived class:
                        DEFINE_SERIALIZABLE( CPosePDFParticles )

                public:
                        void  clear(); //!< Free all the memory associated to m_particles, and set the number of parts = 0

                        /** Constructor
                          * \param M The number of m_particles.
                          */
                        CPosePDFParticles( size_t M = 1 );

                        /** Copy operator, translating if necesary (for example, between m_particles and gaussian representations)
                          */
                        void  copyFrom(const CPosePDF &o) MRPT_OVERRIDE;

                         /** Reset the PDF to a single point: All m_particles will be set exactly to the supplied pose.
                          * \param location The location to set all the m_particles.
                          * \param particlesCount If this is set to 0 the number of m_particles remains unchanged.
                          *  \sa resetUniform, resetUniformFreeSpace, resetAroundSetOfPoses
                          */
                        void  resetDeterministic(
                                const CPose2D &location,
                                size_t particlesCount = 0);

                        /** Reset the PDF to an uniformly distributed one, inside of the defined cube.
                          * If particlesCount is set to -1 the number of m_particles remains unchanged.
                          *  \sa resetDeterministic, resetUniformFreeSpace, resetAroundSetOfPoses
                          */
                        void  resetUniform(
                                const double & x_min,
                                const double & x_max,
                                const double & y_min,
                                const double & y_max,
                                const double & phi_min = -M_PI,
                                const double & phi_max = M_PI,
                                const int       &particlesCount = -1);

                        /** Reset the PDF to a multimodal distribution over a set of "spots" (x,y,phi)
                          * The total number of particles will be `list_poses.size() * num_particles_per_pose`.
                          * \param[in] list_poses The poses (x,y,phi) around which particles will be spread. Must contains at least one pose.
                          * \param[in] num_particles_per_pose Number of particles to be spread around each of the "spots" in list_poses. Must be >=1.
                          * 
                          * Particles will be spread uniformly in a box of width `spread_{x,y,phi_rad}` in each of 
                          * the three coordinates (meters, radians), so it can be understood as the "initial uncertainty".
                          *
                          *  \sa resetDeterministic, resetUniformFreeSpace
                          */
                        void  resetAroundSetOfPoses(
                                const std::vector<mrpt::math::TPose2D> & list_poses,
                                const size_t num_particles_per_pose,
                                const double spread_x,
                                const double spread_y,
                                const double spread_phi_rad);

                         /** Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF).
                           * \sa getCovariance
                           */
                        void getMean(CPose2D &mean_pose) const MRPT_OVERRIDE;

                        /** Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once.
                          * \sa getMean
                          */
                        void getCovarianceAndMean(mrpt::math::CMatrixDouble33 &cov,CPose2D &mean_point) const MRPT_OVERRIDE;

                        /** Returns the pose of the i'th particle.
                          */
                        CPose2D  getParticlePose(size_t i) const;

                        /** Save PDF's m_particles to a text file. In each line it will go: "x y phi weight"
                         */
                        void  saveToTextFile(const std::string &file) const MRPT_OVERRIDE;

                        /** Get the m_particles count (equivalent to "particlesCount")
                         */
                        inline size_t  size() const { return m_particles.size(); }

                        /** this = p (+) this. This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which
                          *   "to project" the current pdf. Result PDF substituted the currently stored one in the object.
                          */
                        void  changeCoordinatesReference( const CPose3D &newReferenceBase ) MRPT_OVERRIDE;

                        /** Draws a single sample from the distribution (WARNING: weights are assumed to be normalized!)
                          */
                        void  drawSingleSample(CPose2D &outPart ) const MRPT_OVERRIDE;

                        /** Appends (pose-composition) a given pose "p" to each particle
                          */
                        void  operator += ( const CPose2D &Ap);

                        /** Appends (add to the list) a set of m_particles to the existing ones, and then normalize weights.
                          */
                        void  append( CPosePDFParticles &o );

                        /** Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF
                          */
                        void     inverse(CPosePDF &o) const MRPT_OVERRIDE;

                        /** Returns the particle with the highest weight.
                          */
                        CPose2D  getMostLikelyParticle() const;

                        /** Bayesian fusion.
                          */
                        void  bayesianFusion( const CPosePDF &p1,const  CPosePDF &p2, const double & minMahalanobisDistToDrop = 0 ) MRPT_OVERRIDE;

                        /** Evaluates the PDF at a given arbitrary point as reconstructed by a Parzen window.
                          * \sa saveParzenPDFToTextFile
                          */
                        double  evaluatePDF_parzen(
                                const double &  x,
                                const double &  y,
                                const double &  phi,
                                const double &  stdXY,
                                const double &  stdPhi ) const;

                        /** Save a text file (compatible with matlab) representing the 2D evaluation of the PDF as reconstructed by a Parzen window.
                          * \sa evaluatePDF_parzen
                          */
                        void  saveParzenPDFToTextFile(
                                const char              *fileName,
                                const double &                  x_min,
                                const double &                  x_max,
                                const double &                  y_min,
                                const double &                  y_max,
                                const double &                  phi,
                                const double &                  stepSizeXY,
                                const double &                  stdXY,
                                const double &                  stdPhi ) const;

                }; // End of class def.
                DEFINE_SERIALIZABLE_POST_CUSTOM_BASE( CPosePDFParticles , CPosePDF )

        } // End of namespace
} // End of namespace

#endif