CRandomFieldGridMap3D.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 |
   +------------------------------------------------------------------------+ */
 
#pragma once
 
#include <mrpt/containers/CDynamicGrid3D.h>
#include <mrpt/math/types_math.h>
#include <mrpt/serialization/CSerializable.h>
#include <mrpt/config/CLoadableOptions.h>
#include <mrpt/system/COutputLogger.h>
#include <mrpt/graphs/ScalarFactorGraph.h>
#include <mrpt/math/lightweight_geom_data.h>
 
// Fwdr decl:
class vtkStructuredGrid;
 
namespace mrpt::maps
{
/** The contents of each voxel in a CRandomFieldGridMap3D map.
  * \ingroup mrpt_maps_grp
 **/
#if defined(MRPT_IS_X86_AMD64)  // Pragma defined to ensure no structure
// packing: since we'll serialize
// TRandomFieldVoxel to streams, we want it not
// to depend on compiler options, etc.
#pragma pack(push, 1)
#endif
struct TRandomFieldVoxel
{
    /** Mean and sigma (standard deviation) estimated values for the voxel. */
    double mean_value, stddev_value;
 
    /** Constructor */
    TRandomFieldVoxel(double _mean_value = .0, double _stddev_value = .0)
        : mean_value(_mean_value), stddev_value(_stddev_value)
    {
    }
};
#if defined(MRPT_IS_X86_AMD64)
#pragma pack(pop)
#endif
 
/** CRandomFieldGridMap3D represents a 3D regular grid where each voxel is
 * associated one real-valued property which is to be estimated by this class.
  *
  *  This class implements a Gaussian Markov Random Field (GMRF) estimator, with
 * each voxel being connected to its
  *   6 immediate neighbors (Up, down, left, right, front, back).
  *  - See papers:
  *    - "Time-variant gas distribution mapping with obstacle information",
 * Monroy, J. G., Blanco, J. L., & Gonzalez-Jimenez, J. Autonomous Robots,
 * 40(1), 1-16, 2016.
  *
  *  Note that this class does not derive from mrpt::maps::CMetricMap since the
 * estimated values do not have sensor-especific semantics,
  *  i.e. the grid can be used to estimate temperature, gas concentration, etc.
  *
  *  Usage:
  *  - Define grid size with either constructor or via `setSize()`.
  *  - Initialize the map with `initialize()`. This resets the contents of the
 * map, so previously-added observations will be lost.
  *  - Add observations of 3D voxels with `insertIndividualReading()`
  *
  * Custom connectivity patterns can be defined with setVoxelsConnectivity().
  *
  * \sa mrpt::maps::CRandomFieldGridMap3D
  * \ingroup mrpt_maps_grp
  * \note [New in MRPT 1.5.0]
  */
class CRandomFieldGridMap3D
    : public mrpt::containers::CDynamicGrid3D<TRandomFieldVoxel>,
      public mrpt::serialization::CSerializable,
      public mrpt::system::COutputLogger
{
    using BASE = mrpt::containers::CDynamicGrid3D<TRandomFieldVoxel>;
 
    DEFINE_SERIALIZABLE(CRandomFieldGridMap3D)
   public:
    /** [default:false] Enables a profiler to show a performance report at
     * application end. */
    static bool ENABLE_GMRF_PROFILER;
 
    /** Constructor.
      * If you set call_initialize_now to false, the object will be initialized
     * immediately (without the heavy initialization of the GMRF),
      * but you then must call `setSize()` or `clear()` later to properly
     * initialize the object before using it to insert observations.
      */
    CRandomFieldGridMap3D(
        double x_min = -2, double x_max = 2, double y_min = -2,
        double y_max = 2, double z_min = -2, double z_max = 2,
        double voxel_size = 0.5, bool call_initialize_now = true);
 
    /** Erases all added observations and start again with an empty gridmap. */
    void clear() override;
 
    /** Save the current estimated mean values to a CSV file (compatible with
     * Paraview) with fields `x y z mean_value`.
      * Optionally, std deviations can be also saved to another file with fields
     * `x y z stddev_value`, if `filName_stddev` is provided.
      * \return false on error writing to file
      * \sa saveAsVtkStructuredGrid
      */
    bool saveAsCSV(
        const std::string& filName_mean,
        const std::string& filName_stddev = std::string()) const;
 
    /** Save the current estimated grid to a VTK file (.vts) as a "structured
     * grid". \sa saveAsCSV */
    bool saveAsVtkStructuredGrid(const std::string& fil) const;
 
    /** Parameters common to any derived class.
      *  Derived classes should derive a new struct from this one, plus "public
     * utils::CLoadableOptions",
      *  and call the internal_* methods where appropiate to deal with the
     * variables declared here.
      *  Derived classes instantions of their "TInsertionOptions" MUST set the
     * pointer "m_insertOptions_common" upon construction.
      */
    struct TInsertionOptions : public mrpt::config::CLoadableOptions
    {
        /** Default values loader */
        TInsertionOptions();
 
        /** See utils::CLoadableOptions */
        void loadFromConfigFile(
            const mrpt::config::CConfigFileBase& source,
            const std::string& section);
 
        /** See utils::CLoadableOptions */
        void dumpToTextStream(std::ostream& out) const;
 
        /** @name Gaussian Markov Random Fields method
            @{ */
        /** The information (Lambda) of fixed map constraints */
        double GMRF_lambdaPrior;
        /** (Default:false) Skip the computation of the variance, just compute
         * the mean */
        bool GMRF_skip_variance;
        /** @} */
    };
 
    /** \sa updateMapEstimation() */
    TInsertionOptions insertionOptions;
 
    /** Changes the size of the grid, maintaining previous contents. \sa setSize
     */
    virtual void resize(
        double new_x_min, double new_x_max, double new_y_min, double new_y_max,
        double new_z_min, double new_z_max,
        const TRandomFieldVoxel& defaultValueNewvoxels,
        double additionalMarginMeters = 2.0) override;
 
    /** Changes the size of the grid, erasing previous contents.If
     * `resolution_z`<0, the same resolution will be used for all dimensions
     * x,y,z as given in `resolution_xy` \sa resize.*/
    virtual void setSize(
        const double x_min, const double x_max, const double y_min,
        const double y_max, const double z_min, const double z_max,
        const double resolution_xy, const double resolution_z = -1.0,
        const TRandomFieldVoxel* fill_value = nullptr) override;
 
    /** Base class for user-supplied objects capable of describing voxels
     * connectivity, used to build prior factors of the MRF graph. \sa
     * setvoxelsConnectivity() */
    struct ConnectivityDescriptor
    {
        using Ptr = std::shared_ptr<ConnectivityDescriptor>;
        // Virtual destructor for polymorphic type.
        virtual ~ConnectivityDescriptor() {}
        /** Implement the check of whether node i=(icx,icy,icz) is connected
        * with node j=(jcx,jcy,jcy).
        * This visitor method will be called only for immediate neighbors.
        * \return true if connected (and the "information" value should be also
        * updated in out_edge_information), false otherwise.
        */
        virtual bool getEdgeInformation(
            /** The parent map on which we are running */
            const CRandomFieldGridMap3D* parent,
            /** (cx,cy,cz) for node "i" */
            size_t icx, size_t icy, size_t icz,
            /** (cx,cy,cz) for node "j" */
            size_t jcx, size_t jcy, size_t jcz,
            /** Must output here the inverse of the variance of the constraint
               edge. */
            double& out_edge_information) = 0;
    };
 
    /** Sets a custom object to define the connectivity between voxels. Must
     * call clear() or setSize() afterwards for the changes to take place. */
    void setVoxelsConnectivity(
        const ConnectivityDescriptor::Ptr& new_connectivity_descriptor);
 
    enum TVoxelInterpolationMethod
    {
        gimNearest = 0,
        gimBilinear
    };
 
    /** Direct update of the map with a reading in a given position of the map.
      * \return false if point is out of the grid extension.
      */
    bool insertIndividualReading(
        /** [in] The value observed in the (x,y,z) position */
        const double sensorReading,
        /** [in] The variance of the sensor observation */
        const double sensorVariance,
        /** [in] The (x,y,z) location */
        const mrpt::math::TPoint3D& point,
        /** [in] Voxel interpolation method: how many voxels will be
           affected by the reading */
        const TVoxelInterpolationMethod method,
        /** [in] Run a global map update after inserting this observation
           (algorithm-dependant) */
        const bool update_map);
 
    /** Run the method-specific procedure required to ensure that the mean &
     * variances are up-to-date with all inserted observations, using parameters
     * in insertionOptions */
    void updateMapEstimation();
 
    /** Returns the 3D grid contents as an VTK grid. */
    void getAsVtkStructuredGrid(
        vtkStructuredGrid* output,
        const std::string& label_mean = std::string("mean"),
        const std::string& label_stddev = std::string("stddev")) const;
 
   protected:
    /** Internal: called called after each change of resolution, size, etc. to
     * build the prior factor information */
    void internal_initialize(bool erase_prev_contents = true);
 
    /** Empty: default */
    ConnectivityDescriptor::Ptr m_gmrf_connectivity;
 
    mrpt::graphs::ScalarFactorGraph m_gmrf;
 
    struct TObservationGMRF
        : public mrpt::graphs::ScalarFactorGraph::UnaryFactorVirtualBase
    {
        /** Observation value */
        double obsValue;
        /** "Information" of the observation (=inverse of the variance) */
        double Lambda;
 
        double evaluateResidual() const override;
        double getInformation() const override;
        void evalJacobian(double& dr_dx) const override;
 
        TObservationGMRF(CRandomFieldGridMap3D& parent)
            : obsValue(.0), Lambda(.0), m_parent(&parent)
        {
        }
 
       private:
        CRandomFieldGridMap3D* m_parent;
    };
 
    struct TPriorFactorGMRF
        : public mrpt::graphs::ScalarFactorGraph::BinaryFactorVirtualBase
    {
        /** "Information" of the observation (=inverse of the variance) */
        double Lambda;
 
        double evaluateResidual() const override;
        double getInformation() const override;
        void evalJacobian(double& dr_dx_i, double& dr_dx_j) const override;
 
        TPriorFactorGMRF(CRandomFieldGridMap3D& parent)
            : Lambda(.0), m_parent(&parent)
        {
        }
 
       private:
        CRandomFieldGridMap3D* m_parent;
    };
 
    /** Vector with the active observations and their respective Information,
     * for each map cell. */
    std::vector<std::deque<TObservationGMRF>> m_mrf_factors_activeObs;
    /** Vector with the precomputed priors for each GMRF model */
    std::deque<TPriorFactorGMRF> m_mrf_factors_priors;
};
 
}