class mrpt::poses::CPosePDFGrid
Overview
Declares a class that represents a Probability Distribution function (PDF) of a 2D pose (x,y,phi).
This class implements that PDF using a 3D grid.
See also:
CPose2D, CPosePDF, CPose2DGridTemplate
#include <mrpt/poses/CPosePDFGrid.h> class CPosePDFGrid: public mrpt::poses::CPosePDF, public mrpt::poses::CPose2DGridTemplate { public: // construction CPosePDFGrid( double xMin = -1.0f, double xMax = 1.0f, double yMin = -1.0f, double yMax = 1.0f, double resolutionXY = 0.5f, double resolutionPhi = mrpt::DEG2RAD(180.0), double phiMin = -M_PI, double phiMax = M_PI ); // methods virtual void copyFrom(const CPosePDF& o); void normalize(); void uniformDistribution(); void getMean(CPose2D& mean_pose) const; virtual std::tuple<cov_mat_t, type_value> getCovarianceAndMean() const; virtual bool saveToTextFile(const std::string& dataFile) const; virtual void changeCoordinatesReference(const CPose3D& newReferenceBase); virtual void bayesianFusion(const CPosePDF& p1, const CPosePDF& p2, const double minMahalanobisDistToDrop = 0); virtual void inverse(CPosePDF& o) const; void drawSingleSample(CPose2D& outPart) const; virtual void drawManySamples(size_t N, std::vector<mrpt::math::CVectorDouble>& outSamples) const; double getXMax() const; double getYMin() const; double getYMax() const; double getPhiMin() const; double getPhiMax() const; double getResolutionXY() const; double getResolutionPhi() const; size_t getSizeX() const; size_t getSizeY() const; size_t getSizePhi() const; };
Inherited Members
public: // typedefs typedef CProbabilityDensityFunction<TDATA, STATE_LEN> self_t; // methods virtual void copyFrom(const CPosePDF& o) = 0; virtual void bayesianFusion(const CPosePDF& p1, const CPosePDF& p2, const double minMahalanobisDistToDrop = 0) = 0; virtual void inverse(CPosePDF& o) const = 0; virtual void changeCoordinatesReference(const CPose3D& newReferenceBase) = 0; size_t x2idx(double x) const; size_t y2idx(double y) const; size_t phi2idx(double phi) const; double idx2x(size_t x) const; double idx2y(size_t y) const; double idx2phi(size_t phi) const; void setSize( double xMin, double xMax, double yMin, double yMax, double resolutionXY, double resolutionPhi, double phiMin = -M_PI, double phiMax = M_PI ); const T* getByPos(double x, double y, double phi) const; T* getByPos(double x, double y, double phi); const T* getByIndex(size_t x, size_t y, size_t phi) const; T* getByIndex(size_t x, size_t y, size_t phi); template <class MATRIXLIKE> void getAsMatrix(double phi, MATRIXLIKE& outMat); double getXMin() const;
Construction
CPosePDFGrid( double xMin = -1.0f, double xMax = 1.0f, double yMin = -1.0f, double yMax = 1.0f, double resolutionXY = 0.5f, double resolutionPhi = mrpt::DEG2RAD(180.0), double phiMin = -M_PI, double phiMax = M_PI )
Constructor: Initializes a, uniform distribution over the whole given range.
Methods
virtual void copyFrom(const CPosePDF& o)
Copy operator, translating if necesary (for example, between particles and gaussian representations)
void normalize()
Normalizes the PDF, such as all cells sum the unity.
void uniformDistribution()
Assigns the same value to all the cells in the grid, so the sum 1.
virtual std::tuple<cov_mat_t, type_value> getCovarianceAndMean() const
Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.
See also:
virtual bool saveToTextFile(const std::string& dataFile) const
Save the contents of the 3D grid in one file, as a vertical concatenation of rectangular matrix for the different “PHI” discrete levels, and the size in X,Y,and PHI in another file named “<filename>_dims.txt”.
Returns:
false on error
virtual void changeCoordinatesReference(const CPose3D& newReferenceBase)
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.
virtual void bayesianFusion( const CPosePDF& p1, const CPosePDF& p2, const double minMahalanobisDistToDrop = 0 )
Bayesian fusion of 2 densities (In the grid representation this becomes a pointwise multiplication)
virtual void inverse(CPosePDF& o) const
Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF.
void drawSingleSample(CPose2D& outPart) const
Draws a single sample from the distribution (WARNING: weights are assumed to be normalized!)
virtual void drawManySamples(size_t N, std::vector<mrpt::math::CVectorDouble>& outSamples) const
Draws a number of samples from the distribution, and saves as a list of 1x3 vectors, where each row contains a (x,y,phi) datum.