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CPosePDFGaussianInf.h
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1 /* +---------------------------------------------------------------------------+
2  | Mobile Robot Programming Toolkit (MRPT) |
3  | http://www.mrpt.org/ |
4  | |
5  | Copyright (c) 2005-2016, Individual contributors, see AUTHORS file |
6  | See: http://www.mrpt.org/Authors - All rights reserved. |
7  | Released under BSD License. See details in http://www.mrpt.org/License |
8  +---------------------------------------------------------------------------+ */
9 #ifndef CPosePDFGaussianInf_H
10 #define CPosePDFGaussianInf_H
11 
12 #include <mrpt/poses/CPosePDF.h>
14 
15 namespace mrpt
16 {
17 namespace poses
18 {
19  class CPose3DPDF;
20 
21  // This must be added to any CSerializable derived class:
22  DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE( CPosePDFGaussianInf, CPosePDF )
23 
24  /** A Probability Density function (PDF) of a 2D pose \f$ p(\mathbf{x}) = [x ~ y ~ \phi ]^t \f$ as a Gaussian with a mean and the inverse of the covariance.
25  *
26  * This class implements a PDF as a mono-modal Gaussian distribution in its <b>information form</b>, that is,
27  * keeping the inverse of the covariance matrix instead of the covariance matrix itself.
28  *
29  * This class is the dual of CPosePDFGaussian.
30  *
31  * \sa CPose2D, CPosePDF, CPosePDFParticles
32  * \ingroup poses_pdf_grp
33  */
35  {
36  // This must be added to any CSerializable derived class:
38 
39  protected:
40  /** Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!)
41  */
42  void assureSymmetry();
43 
44  public:
45  /** @name Data fields
46  @{ */
47 
48  CPose2D mean; //!< The mean value
49  mrpt::math::CMatrixDouble33 cov_inv; //!< The inverse of the 3x3 covariance matrix (the "information" matrix)
50 
51  /** @} */
52 
53  inline const CPose2D & getPoseMean() const { return mean; }
54  inline CPose2D & getPoseMean() { return mean; }
55 
56  /** Default constructor (mean=all zeros, inverse covariance=all zeros -> so be careful!) */
58 
59  /** Constructor with a mean value (inverse covariance=all zeros -> so be careful!) */
60  explicit CPosePDFGaussianInf( const CPose2D &init_Mean );
61 
62  /** Constructor */
63  CPosePDFGaussianInf( const CPose2D &init_Mean, const mrpt::math::CMatrixDouble33 &init_CovInv );
64 
65  /** Copy constructor, including transformations between other PDFs */
66  explicit CPosePDFGaussianInf( const CPosePDF &o ) { copyFrom( o ); }
67 
68  /** Copy constructor, including transformations between other PDFs */
69  explicit CPosePDFGaussianInf( const CPose3DPDF &o ) { copyFrom( o ); }
70 
71  /** Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF).
72  * \sa getCovariance */
73  void getMean(CPose2D &mean_pose) const MRPT_OVERRIDE {
74  mean_pose = mean;
75  }
76 
77  /** Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once.
78  * \sa getMean */
80  mean_point = mean;
81  this->cov_inv.inv(cov);
82  }
83 
84  /** Returns the information (inverse covariance) matrix (a STATE_LEN x STATE_LEN matrix) \sa getMean, getCovarianceAndMean */
85  virtual void getInformationMatrix(mrpt::math::CMatrixDouble33 &inf) const MRPT_OVERRIDE { inf=cov_inv; }
86 
87  /** Copy operator, translating if necesary (for example, between particles and gaussian representations) */
88  void copyFrom(const CPosePDF &o) MRPT_OVERRIDE;
89 
90  /** Copy operator, translating if necesary (for example, between particles and gaussian representations) */
91  void copyFrom(const CPose3DPDF &o);
92 
93  /** Save PDF's particles to a text file, containing the 2D pose in the first line, then the covariance matrix in next 3 lines. */
94  void saveToTextFile(const std::string &file) const MRPT_OVERRIDE;
95 
96  /** this = p (+) this. This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which
97  * "to project" the current pdf. Result PDF substituted the currently stored one in the object */
98  void changeCoordinatesReference( const CPose3D &newReferenceBase ) MRPT_OVERRIDE;
99 
100  /** this = p (+) this. This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which
101  * "to project" the current pdf. Result PDF substituted the currently stored one in the object. */
102  void changeCoordinatesReference( const CPose2D &newReferenceBase );
103 
104  /** Rotate the covariance matrix by replacing it by \f$ \mathbf{R}~\mathbf{COV}~\mathbf{R}^t \f$, where \f$ \mathbf{R} = \left[ \begin{array}{ccc} \cos\alpha & -\sin\alpha & 0 \\ \sin\alpha & \cos\alpha & 0 \\ 0 & 0 & 1 \end{array}\right] \f$. */
105  void rotateCov(const double ang);
106 
107  /** Set \f$ this = x1 \ominus x0 \f$ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (For 'x0' and 'x1' being independent variables!). */
108  void inverseComposition( const CPosePDFGaussianInf &x, const CPosePDFGaussianInf &ref );
109 
110  /** Set \f$ this = x1 \ominus x0 \f$ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (Given the 3x3 cross-covariance matrix of variables x0 and x1). */
111  void inverseComposition(
112  const CPosePDFGaussianInf &x1,
113  const CPosePDFGaussianInf &x0,
114  const mrpt::math::CMatrixDouble33 &COV_01
115  );
116 
117  /** Draws a single sample from the distribution */
118  void drawSingleSample( CPose2D &outPart ) const MRPT_OVERRIDE;
119 
120  /** 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. */
121  void drawManySamples( size_t N, std::vector<mrpt::math::CVectorDouble> & outSamples ) const MRPT_OVERRIDE;
122 
123  /** Bayesian fusion of two points gauss. distributions, then save the result in this object.
124  * The process is as follows:<br>
125  * - (x1,S1): Mean and variance of the p1 distribution.
126  * - (x2,S2): Mean and variance of the p2 distribution.
127  * - (x,S): Mean and variance of the resulting distribution.
128  *
129  * S = (S1<sup>-1</sup> + S2<sup>-1</sup>)<sup>-1</sup>;
130  * x = S * ( S1<sup>-1</sup>*x1 + S2<sup>-1</sup>*x2 );
131  */
132  void bayesianFusion(const CPosePDF &p1,const CPosePDF &p2, const double &minMahalanobisDistToDrop = 0 ) MRPT_OVERRIDE;
133 
134  /** Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF */
135  void inverse(CPosePDF &o) const MRPT_OVERRIDE;
136 
137  /** Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated). */
138  void operator += ( const CPose2D &Ap);
139 
140  /** Evaluates the PDF at a given point */
141  double evaluatePDF( const CPose2D &x ) const;
142 
143  /** Evaluates the ratio PDF(x) / PDF(MEAN), that is, the normalized PDF in the range [0,1]. */
144  double evaluateNormalizedPDF( const CPose2D &x ) const;
145 
146  /** Computes the Mahalanobis distance between the centers of two Gaussians. */
147  double mahalanobisDistanceTo( const CPosePDFGaussianInf& theOther );
148 
149  /** Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated) (see formulas in jacobiansPoseComposition ). */
150  void operator += ( const CPosePDFGaussianInf &Ap);
151 
152  /** Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition (both the mean, and the covariance matrix are updated) */
153  inline void operator -=( const CPosePDFGaussianInf &ref ) {
154  this->inverseComposition(*this,ref);
155  }
156 
157  }; // End of class def.
158  DEFINE_SERIALIZABLE_POST_CUSTOM_BASE( CPosePDFGaussianInf, CPosePDF )
159 
160  bool BASE_IMPEXP operator==(const CPosePDFGaussianInf &p1,const CPosePDFGaussianInf &p2);
161  /** Pose compose operator: RES = A (+) B , computing both the mean and the covariance */
162  CPosePDFGaussianInf BASE_IMPEXP operator +( const CPosePDFGaussianInf &a, const CPosePDFGaussianInf &b );
163  /** Pose inverse compose operator: RES = A (-) B , computing both the mean and the covariance */
164  CPosePDFGaussianInf BASE_IMPEXP operator -( const CPosePDFGaussianInf &a, const CPosePDFGaussianInf &b );
165  /** Returns the Gaussian distribution of \f$ \mathbf{C} \f$, for \f$ \mathbf{C} = \mathbf{A} \oplus \mathbf{B} \f$. */
167 
168  /** Dumps the mean and covariance matrix to a text stream. */
169  std::ostream BASE_IMPEXP & operator << (std::ostream & out, const CPosePDFGaussianInf& obj);
170 
171  } // End of namespace
172 } // End of namespace
173 
174 #endif
mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf
CPosePDFGaussianInf(const CPose3DPDF &o)
Copy constructor, including transformations between other PDFs.
Definition: CPosePDFGaussianInf.h:69
mrpt::poses::operator-
CPose2D BASE_IMPEXP operator-(const CPose2D &p)
Unary - operator: return the inverse pose "-p" (Note that is NOT the same than a pose with negative x...
mrpt::poses::CPosePDFGaussianInf::getPoseMean
CPose2D & getPoseMean()
Definition: CPosePDFGaussianInf.h:54
CMatrixFixedNumeric.h
DEFINE_SERIALIZABLE_POST_CUSTOM_BASE
#define DEFINE_SERIALIZABLE_POST_CUSTOM_BASE(class_name, base_name)
Definition: CSerializable.h:182
mrpt::poses::CPose3DPDF
Declares a class that represents a Probability Density Function (PDF) of a 3D pose (6D actually).
Definition: CPose3DPDF.h:40
mrpt::poses::CPosePDFGaussianInf::mean
CPose2D mean
The mean value.
Definition: CPosePDFGaussianInf.h:48
mrpt::poses::CPosePDFGaussianInf::getMean
void getMean(CPose2D &mean_pose) const MRPT_OVERRIDE
Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF).
Definition: CPosePDFGaussianInf.h:73
mrpt
This is the global namespace for all Mobile Robot Programming Toolkit (MRPT) libraries.
Definition: CParticleFilter.h:16
mrpt::pbmap::inverse
Eigen::Matrix< dataType, 4, 4 > inverse(Eigen::Matrix< dataType, 4, 4 > &pose)
Definition: Miscellaneous.h:74
mrpt::poses::operator+
mrpt::math::TPoint2D BASE_IMPEXP operator+(const CPose2D &pose, const mrpt::math::TPoint2D &pnt)
Compose a 2D point from a new coordinate base given by a 2D pose.
saveToTextFile
void saveToTextFile(const std::string &file, mrpt::math::TMatrixTextFileFormat fileFormat=mrpt::math::MATRIX_FORMAT_ENG, bool appendMRPTHeader=false, const std::string &userHeader=std::string()) const
Save matrix to a text file, compatible with MATLAB text format (see also the methods of matrix classe...
mrpt::poses::CPosePDFGaussianInf::cov_inv
mrpt::math::CMatrixDouble33 cov_inv
The inverse of the 3x3 covariance matrix (the "information" matrix)
Definition: CPosePDFGaussianInf.h:49
mrpt::poses::CPosePDFGaussianInf::getCovarianceAndMean
void getCovarianceAndMean(mrpt::math::CMatrixDouble33 &cov, CPose2D &mean_point) const MRPT_OVERRIDE
Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once.
Definition: CPosePDFGaussianInf.h:79
CPosePDF.h
mrpt::poses::CPose2D
A class used to store a 2D pose.
Definition: CPose2D.h:36
mrpt::poses::CPose3D
A class used to store a 3D pose (a 3D translation + a rotation in 3D).
Definition: CPose3D.h:72
mrpt::poses::CPosePDFGaussianInf
A Probability Density function (PDF) of a 2D pose as a Gaussian with a mean and the inverse of the c...
Definition: CPosePDFGaussianInf.h:34
mrpt::math::CMatrixFixedNumeric
A numeric matrix of compile-time fixed size.
Definition: CMatrixFixedNumeric.h:34
mrpt::poses::CPosePDF
Declares a class that represents a probability density function (pdf) of a 2D pose (x,...
Definition: CPosePDF.h:39
mrpt::poses::CPosePDFGaussianInf::getInformationMatrix
virtual void getInformationMatrix(mrpt::math::CMatrixDouble33 &inf) const MRPT_OVERRIDE
Returns the information (inverse covariance) matrix (a STATE_LEN x STATE_LEN matrix)
Definition: CPosePDFGaussianInf.h:85
mrpt::poses::operator==
bool operator==(const CPoint< DERIVEDCLASS > &p1, const CPoint< DERIVEDCLASS > &p2)
Definition: CPoint.h:130
DEFINE_SERIALIZABLE
#define DEFINE_SERIALIZABLE(class_name)
This declaration must be inserted in all CSerializable classes definition, within the class declarati...
Definition: CSerializable.h:147
mean
EIGEN_STRONG_INLINE double mean() const
Computes the mean of the entire matrix.
Definition: eigen_plugins.h:353
mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf
CPosePDFGaussianInf(const CPosePDF &o)
Copy constructor, including transformations between other PDFs.
Definition: CPosePDFGaussianInf.h:66
mrpt::poses::CPosePDFGaussianInf::getPoseMean
const CPose2D & getPoseMean() const
Definition: CPosePDFGaussianInf.h:53
mrpt::poses::operator<<
std::ostream & operator<<(std::ostream &o, const CPoint< DERIVEDCLASS > &p)
Dumps a point as a string [x,y] or [x,y,z]
Definition: CPoint.h:106
mrpt::math::cov
Eigen::Matrix< typename MATRIX::Scalar, MATRIX::ColsAtCompileTime, MATRIX::ColsAtCompileTime > cov(const MATRIX &v)
Computes the covariance matrix from a list of samples in an NxM matrix, where each row is a sample,...
Definition: ops_matrices.h:135
MRPT_OVERRIDE
#define MRPT_OVERRIDE
C++11 "override" for virtuals:
Definition: mrpt_macros.h:28
DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE
#define DEFINE_SERIALIZABLE_PRE_CUSTOM_BASE(class_name, base_name)
This declaration must be inserted in all CSerializable classes definition, before the class declarati...
Definition: CSerializable.h:178



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