CPose3DPDFGaussian.h

Go to the documentation of this file.

/* +------------------------------------------------------------------------+
   |                     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 CPose3DPDFGaussian_H
#define CPose3DPDFGaussian_H

#include <mrpt/poses/CPose3DPDF.h>
#include <mrpt/poses/CPose3D.h>

namespace mrpt
{
namespace poses
{
class CPosePDF;
class CPosePDFGaussian;
class CPose3DQuatPDFGaussian;

/** Declares a class that represents a Probability Density function (PDF) of a
 * 3D pose \f$ p(\mathbf{x}) = [x ~ y ~ z ~ yaw ~ pitch ~ roll]^t \f$.
 *
 *   This class implements that PDF using a mono-modal Gaussian distribution.
 * See mrpt::poses::CPose3DPDF for more details.
 *
 *  Uncertainty of pose composition operations (\f$ y = x \oplus u \f$) is
 * implemented in the method "CPose3DPDFGaussian::operator+=".
 *
 *  For further details on implemented methods and the theory behind them,
 *  see <a
 * href="http://www.mrpt.org/6D_poses:equivalences_compositions_and_uncertainty"
 * >this report</a>.
 *
 * \sa CPose3D, CPose3DPDF, CPose3DPDFParticles
 * \ingroup poses_pdf_grp
 */
class CPose3DPDFGaussian : public CPose3DPDF
{
        DEFINE_SERIALIZABLE(CPose3DPDFGaussian)

   protected:
        /** Assures the symmetry of the covariance matrix (eventually certain
         * operations in the math-coprocessor lead to non-symmetric matrixes!)
          */
        void assureSymmetry();

   public:
        /** Default constructor
         */
        CPose3DPDFGaussian();

        /** Constructor
          */
        explicit CPose3DPDFGaussian(const CPose3D& init_Mean);

        /** Uninitialized constructor: leave all fields uninitialized - Call with
         * UNINITIALIZED_POSE as argument
          */
        CPose3DPDFGaussian(TConstructorFlags_Poses constructor_dummy_param);

        /** Constructor  */
        CPose3DPDFGaussian(
                const CPose3D& init_Mean, const mrpt::math::CMatrixDouble66& init_Cov);

        /** Constructor from a Gaussian 2D pose PDF (sets to 0 the missing variables
         * z,pitch, and roll).
          */
        explicit CPose3DPDFGaussian(const CPosePDFGaussian& o);

        /** Constructor from a 6D pose PDF described as a Quaternion
          */
        explicit CPose3DPDFGaussian(const CPose3DQuatPDFGaussian& o);

        /** The mean value
         */
        CPose3D mean;

        /** The 6x6 covariance matrix
         */
        mrpt::math::CMatrixDouble66 cov;

        inline const CPose3D& getPoseMean() const { return mean; }
        inline CPose3D& getPoseMean() { return mean; }
        /** Returns an estimate of the pose, (the mean, or mathematical expectation
         * of the PDF).
          * \sa getCovariance
          */
        void getMean(CPose3D& mean_pose) const override { mean_pose = mean; }
        /** Returns an estimate of the pose covariance matrix (6x6 cov matrix) and
         * the mean, both at once.
          * \sa getMean
          */
        void getCovarianceAndMean(
                mrpt::math::CMatrixDouble66& out_cov,
                CPose3D& mean_point) const override
        {
                out_cov = this->cov;
                mean_point = this->mean;
        }

        void asString(std::string& s) const;
        inline std::string asString() const
        {
                std::string s;
                asString(s);
                return s;
        }

        /** Copy operator, translating if necesary (for example, between particles
         * and gaussian representations)
          */
        void copyFrom(const CPose3DPDF& o) override;

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

        /** Copy from a 6D pose PDF described as a Quaternion
          */
        void copyFrom(const CPose3DQuatPDFGaussian& o);

        /** Save the PDF to a text file, containing the 3D pose in the first line,
         * then the covariance matrix in next 3 lines.
         */
        void saveToTextFile(const std::string& file) const override;

        /** 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) override;

        /** Draws a single sample from the distribution
          */
        void drawSingleSample(CPose3D& outPart) const override;

        /** Draws a number of samples from the distribution, and saves as a list of
         * 1x6 vectors, where each row contains a (x,y,phi) datum.
          */
        void drawManySamples(
                size_t N,
                std::vector<mrpt::math::CVectorDouble>& outSamples) const override;

        /** Bayesian fusion of two points gauss. distributions, then save the result
          *in this object.
          *  The process is as follows:<br>
          *             - (x1,S1): Mean and variance of the p1 distribution.
          *             - (x2,S2): Mean and variance of the p2 distribution.
          *             - (x,S): Mean and variance of the resulting distribution.
          *
          *    S = (S1<sup>-1</sup> + S2<sup>-1</sup>)<sup>-1</sup>;
          *    x = S * ( S1<sup>-1</sup>*x1 + S2<sup>-1</sup>*x2 );
          */
        void bayesianFusion(const CPose3DPDF& p1, const CPose3DPDF& p2) override;

        /** Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF
          */
        void inverse(CPose3DPDF& o) const override;

        /** Unary - operator, returns the PDF of the inverse pose.  */
        inline CPose3DPDFGaussian operator-() const
        {
                CPose3DPDFGaussian p(UNINITIALIZED_POSE);
                this->inverse(p);
                return p;
        }

        /** Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the
         * mean, and the covariance matrix are updated).
          */
        void operator+=(const CPose3D& Ap);

        /** Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the
         * mean, and the covariance matrix are updated).
          */
        void operator+=(const CPose3DPDFGaussian& Ap);

        /** Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition
         * (both the mean, and the covariance matrix are updated).
          */
        void operator-=(const CPose3DPDFGaussian& Ap);

        /** Evaluates the PDF at a given point.
          */
        double evaluatePDF(const CPose3D& x) const;

        /** Evaluates the ratio PDF(x) / PDF(MEAN), that is, the normalized PDF in
         * the range [0,1].
          */
        double evaluateNormalizedPDF(const CPose3D& x) const;

        /** Computes the Mahalanobis distance between the centers of two Gaussians.
          *  The variables with a variance exactly equal to 0 are not taken into
         * account in the process, but
          *   "infinity" is returned if the corresponding elements are not exactly
         * equal.
          */
        double mahalanobisDistanceTo(const CPose3DPDFGaussian& theOther);

        /** Returns a 3x3 matrix with submatrix of the covariance for the variables
         * (x,y,yaw) only.
          */
        void getCovSubmatrix2D(mrpt::math::CMatrixDouble& out_cov) const;

};  // End of class def.
/** Pose composition for two 3D pose Gaussians  \sa CPose3DPDFGaussian::operator
 * +=  */
inline CPose3DPDFGaussian operator+(
        const CPose3DPDFGaussian& x, const CPose3DPDFGaussian& u)
{
        CPose3DPDFGaussian res(x);
        res += u;
        return res;
}

/** Pose composition for two 3D pose Gaussians  \sa CPose3DPDFGaussian::operator
 * -=  */
inline CPose3DPDFGaussian operator-(
        const CPose3DPDFGaussian& x, const CPose3DPDFGaussian& u)
{
        CPose3DPDFGaussian res(x);
        res -= u;
        return res;
}

/** Dumps the mean and covariance matrix to a text stream.
  */
std::ostream& operator<<(std::ostream& out, const CPose3DPDFGaussian& obj);

bool operator==(const CPose3DPDFGaussian& p1, const CPose3DPDFGaussian& p2);

}  // End of namespace

/** Global variables to change the run-time behaviour of some MRPT classes
 * within mrpt-base.
  *  See each variable for the description of what classes it affects.
  */
namespace global_settings
{
/** If set to true (false), a Scaled Unscented Transform is used instead of a
  *linear approximation with Jacobians.
  * Affects to:
  *             - CPose3DPDFGaussian::CPose3DPDFGaussian( const CPose3DQuatPDFGaussian
  *&o)
  */
void USE_SUT_QUAT2EULER_CONVERSION(bool value);
bool USE_SUT_QUAT2EULER_CONVERSION();
}

}  // End of namespace

#endif