CPosePDF.h

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/* +---------------------------------------------------------------------------+
   |          The Mobile Robot Programming Toolkit (MRPT) C++ library          |
   |                                                                           |
   |                       http://www.mrpt.org/                                |
   |                                                                           |
   |   Copyright (C) 2005-2011  University of Malaga                           |
   |                                                                           |
   |    This software was written by the Machine Perception and Intelligent    |
   |      Robotics Lab, University of Malaga (Spain).                          |
   |    Contact: Jose-Luis Blanco  <jlblanco@ctima.uma.es>                     |
   |                                                                           |
   |  This file is part of the MRPT project.                                   |
   |                                                                           |
   |     MRPT is free software: you can redistribute it and/or modify          |
   |     it under the terms of the GNU General Public License as published by  |
   |     the Free Software Foundation, either version 3 of the License, or     |
   |     (at your option) any later version.                                   |
   |                                                                           |
   |   MRPT is distributed in the hope that it will be useful,                 |
   |     but WITHOUT ANY WARRANTY; without even the implied warranty of        |
   |     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the         |
   |     GNU General Public License for more details.                          |
   |                                                                           |
   |     You should have received a copy of the GNU General Public License     |
   |     along with MRPT.  If not, see <http://www.gnu.org/licenses/>.         |
   |                                                                           |
   +---------------------------------------------------------------------------+ */
#ifndef CPOSEPDF_H
#define CPOSEPDF_H

#include <mrpt/utils/CSerializable.h>
#include <mrpt/poses/CPose2D.h>
#include <mrpt/math/CMatrixTemplateNumeric.h>
#include <mrpt/utils/CProbabilityDensityFunction.h>


namespace mrpt
{
namespace poses
{
        using namespace mrpt::math;

        // This must be added to any CSerializable derived class:
        DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE( CPosePDF, mrpt::utils::CSerializable )

        /** Declares a class that represents a probability density function (pdf) of a 2D pose (x,y,phi).
         *   This class is just the base class for unifying many diferent ways this pdf can be implemented.
         *
         *  For convenience, a pose composition is also defined for any pdf derived class,
         *   changeCoordinatesReference, in the form of a method rather than an operator.
         *
         *
         *  See also the tutorial on <a href="http://www.mrpt.org/Probability_Density_Distributions_Over_Spatial_Representations" >probabilistic spatial representations in the MRPT</a>.
         *
         * \sa CPose2D, CPose3DPDF, CPoseRandomSampler
         * \ingroup poses_pdf_grp
         */
        class BASE_IMPEXP CPosePDF : public mrpt::utils::CSerializable, public mrpt::utils::CProbabilityDensityFunction<CPose2D,3>
        {
                DEFINE_VIRTUAL_SERIALIZABLE( CPosePDF )

        public:
                /** Copy operator, translating if necesary (for example, between particles and gaussian representations)
                  */
                virtual void  copyFrom(const CPosePDF &o) = 0;


                /** Bayesian fusion of two pose distributions (product of two distributions->new distribution), then save the result in this object (WARNING: See implementing classes to see classes that can and cannot be mixtured!)
                  * \param p1 The first distribution to fuse
                  * \param p2 The second distribution to fuse
                  * \param minMahalanobisDistToDrop If set to different of 0, the result of very separate Gaussian modes (that will result in negligible components) in SOGs will be dropped to reduce the number of modes in the output.
                  */
                virtual void  bayesianFusion(const  CPosePDF &p1,const  CPosePDF &p2, const double&minMahalanobisDistToDrop = 0)  = 0 ;

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

                enum { is_3D_val = 0 };
                static inline bool is_3D() { return is_3D_val!=0; }
                enum { is_PDF_val = 1 };
                static inline bool is_PDF() { return is_PDF_val!=0; }

                /** Returns a 3D representation of this PDF.
                  * \note Needs the mrpt-opengl library, and using mrpt::opengl::CSetOfObjectsPtr as template argument.
                  */
                template <class OPENGL_SETOFOBJECTSPTR>
                inline void getAs3DObject(OPENGL_SETOFOBJECTSPTR &out_obj) const {
                        typedef typename OPENGL_SETOFOBJECTSPTR::value_type SETOFOBJECTS;
                        *out_obj = *SETOFOBJECTS::posePDF2opengl(*this);
                }

                /** Returns a 3D representation of this PDF.
                  * \note Needs the mrpt-opengl library, and using mrpt::opengl::CSetOfObjectsPtr as template argument.
                  */
                template <class OPENGL_SETOFOBJECTSPTR>
                inline OPENGL_SETOFOBJECTSPTR getAs3DObject() const {
                        typedef typename OPENGL_SETOFOBJECTSPTR::value_type SETOFOBJECTS;
                        return SETOFOBJECTS::posePDF2opengl(*this);
                }


        }; // End of class def.


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

#endif