ndt_matcher_d2d_2d.h

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#ifndef NDT_MATCHER_D2D_2D_HH
#define NDT_MATCHER_D2D_2D_HH

#include <ndt_map/ndt_map.h>
#include "pcl/point_cloud.h"
#include "Eigen/Core"

#include <stdlib.h>
#include <stdio.h>
#include <math.h>

namespace lslgeneric
{

class NDTMatcherD2D_2D
{
public:
    NDTMatcherD2D_2D(bool _isIrregularGrid,
                  bool useDefaultGridResolutions, std::vector<double> _resolutions)
    {
        this->init(_isIrregularGrid,useDefaultGridResolutions,_resolutions);
    }
    NDTMatcherD2D_2D()
    {
        this->init(false,true,std::vector<double>());
    }
    NDTMatcherD2D_2D(const NDTMatcherD2D_2D& other)
    {
        this->init(other.isIrregularGrid,false,other.resolutions);
    }

    bool match( pcl::PointCloud<pcl::PointXYZ>& target,
                pcl::PointCloud<pcl::PointXYZ>& source,
                Eigen::Transform<double,3,Eigen::Affine,Eigen::ColMajor>& T,
                bool useInitialGuess = false);

    bool match( NDTMap& target,
                NDTMap& source,
                Eigen::Transform<double,3,Eigen::Affine,Eigen::ColMajor>& T,
                bool useInitialGuess = false);

    //compute the score gradient & hessian of a point cloud + transformation to an NDT (assuming a 2D transformation)
    // input: moving, fixed, tr, computeHessian
    //output: score_gradient, Hessian, returns: score!
    virtual double derivativesNDT_2d(
        const std::vector<NDTCell*> &source,
        const NDTMap &target,
        Eigen::MatrixXd &score_gradient,
        Eigen::MatrixXd &Hessian,
        bool computeHessian
    );
    double finalscore;
    double current_resolution;
    
    int ITR_MAX;
    bool step_control;
    double DELTA_SCORE;
protected:

    Eigen::Matrix<double,3,3> Jest;
    Eigen::Matrix<double,9,3> Hest;
    Eigen::Matrix<double,3,9> Zest;
    Eigen::Matrix<double,9,9> ZHest;
    //vars for gradient
    Eigen::Matrix<double,3,1> xtBJ, xtBZBx, Q;
    //vars for hessian
    Eigen::Matrix<double,3,3> JtBJ, xtBZBJ, xtBH, xtBZBZBx, xtBZhBx;
    Eigen::Matrix<double,1,3> TMP1, xtB;

    int NUMBER_OF_ACTIVE_CELLS;
    int NUMBER_OF_POINTS;
    double lfd1,lfd2;
    int iteration_counter_internal;
    bool isIrregularGrid;
    std::vector<double> resolutions;

    double normalizeAngle(double a);
    //initializes stuff;
    void init(bool _isIrregularGrid,
              bool useDefaultGridResolutions, std::vector<double> _resolutions);

    //iteratively update the score gradient and hessian
    virtual bool update_gradient_hessian_2d(
        Eigen::MatrixXd &score_gradient,
        Eigen::MatrixXd &Hessian,
        const Eigen::Vector3d &m1,
        const Eigen::Matrix3d &C1,
        const double &likelihood,
        bool computeHessian);

    //pre-computes the derivative matrices Jest, Hest, Zest, ZHest
    void computeDerivatives_2d(Eigen::Vector3d &m1, Eigen::Matrix3d C1, bool computeHessian=true);

    //iteratively update the score gradient and hessian (2d version)
    virtual bool update_gradient_hessian_local_2d(
        Eigen::MatrixXd &score_gradient,
        Eigen::MatrixXd &Hessian,
        const Eigen::Vector3d &m1,
        const Eigen::Matrix3d &C1,
        const double &likelihood,
        const Eigen::Matrix<double,3,3> &_Jest,
        const Eigen::Matrix<double,9,3> &_Hest,
        const Eigen::Matrix<double,3,9> &_Zest,
        const Eigen::Matrix<double,9,9> &_ZHest,
        bool computeHessian);

    //pre-computes the derivative matrices Jest, Hest, Zest, ZHest
    void computeDerivativesLocal_2d(Eigen::Vector3d &m1, Eigen::Matrix3d C1,
                                 Eigen::Matrix<double,3,3> &_Jest,
                                 Eigen::Matrix<double,9,3> &_Hest,
                                 Eigen::Matrix<double,3,9> &_Zest,
                                 Eigen::Matrix<double,9,9> &_ZHest,
                                 bool computeHessian);

    //perform line search to find the best descent rate (Mohre&Thuente)
    //adapted from NOX
    double lineSearch2D(
        Eigen::Matrix<double,3,1> &increment,
        std::vector<NDTCell*> &source,
        NDTMap &target) ;

    //auxiliary functions for MoreThuente line search
    struct MoreThuente
    {
        static double min(double a, double b);
        static double max(double a, double b);
        static double absmax(double a, double b, double c);
        static int cstep(double& stx, double& fx, double& dx,
                         double& sty, double& fy, double& dy,
                         double& stp, double& fp, double& dp,
                         bool& brackt, double stmin, double stmax);
    }; //end MoreThuente
    //perform a subsampling depending on user choice

public:
    EIGEN_MAKE_ALIGNED_OPERATOR_NEW
};

} // end namespace

#endif