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mrpt::poses::CPosePDFGaussian Class Referenceabstract

Detailed Description

Declares a class that represents a Probability Density function (PDF) of a 2D pose $ p(\mathbf{x}) = [x ~ y ~ \phi ]^t $.

This class implements that PDF using a mono-modal Gaussian distribution. See mrpt::poses::CPosePDF for more details.

See also
CPose2D, CPosePDF, CPosePDFParticles

Definition at line 60 of file CPosePDFGaussian.h.

#include <mrpt/poses/CPosePDFGaussian.h>

Inheritance diagram for mrpt::poses::CPosePDFGaussian:
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Public Types

enum  { is_3D_val = 0 }
 
enum  { is_PDF_val = 1 }
 
typedef CPose2D type_value
 The type of the state the PDF represents. More...
 

Public Member Functions

const CPose2DgetPoseMean () const
 
CPose2DgetPoseMean ()
 
 CPosePDFGaussian ()
 Default constructor. More...
 
 CPosePDFGaussian (const CPose2D &init_Mean)
 Constructor. More...
 
 CPosePDFGaussian (const CPose2D &init_Mean, const CMatrixDouble33 &init_Cov)
 Constructor. More...
 
 CPosePDFGaussian (const CPosePDF &o)
 Copy constructor, including transformations between other PDFs. More...
 
 CPosePDFGaussian (const CPose3DPDF &o)
 Copy constructor, including transformations between other PDFs. More...
 
void getMean (CPose2D &mean_pose) const
 Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF). More...
 
void getCovarianceAndMean (CMatrixDouble33 &cov, CPose2D &mean_point) const
 Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once. More...
 
void copyFrom (const CPosePDF &o)
 Copy operator, translating if necesary (for example, between particles and gaussian representations) More...
 
void copyFrom (const CPose3DPDF &o)
 Copy operator, translating if necesary (for example, between particles and gaussian representations) More...
 
void saveToTextFile (const std::string &file) const
 Save PDF's particles to a text file, containing the 2D pose in the first line, then the covariance matrix in next 3 lines. More...
 
void changeCoordinatesReference (const CPose3D &newReferenceBase)
 this = p (+) this. More...
 
void changeCoordinatesReference (const CPose2D &newReferenceBase)
 this = p (+) this. More...
 
void rotateCov (const double ang)
 Rotate the covariance matrix by replacing it by $ \mathbf{R}~\mathbf{COV}~\mathbf{R}^t $, where $ \mathbf{R} = \left[ \begin{array}{ccc} \cos\alpha & -\sin\alpha & 0 \\ \sin\alpha & \cos\alpha & 0 \\ 0 & 0 & 1 \end{array}\right] $. More...
 
void inverseComposition (const CPosePDFGaussian &x, const CPosePDFGaussian &ref)
 Set $ this = x1 \ominus x0 $ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (For 'x0' and 'x1' being independent variables!). More...
 
void inverseComposition (const CPosePDFGaussian &x1, const CPosePDFGaussian &x0, const CMatrixDouble33 &COV_01)
 Set $ this = x1 \ominus x0 $ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (Given the 3x3 cross-covariance matrix of variables x0 and x1). More...
 
void drawSingleSample (CPose2D &outPart) const
 Draws a single sample from the distribution. More...
 
void drawManySamples (size_t N, std::vector< vector_double > &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. More...
 
void bayesianFusion (const CPosePDF &p1, const CPosePDF &p2, const double &minMahalanobisDistToDrop=0)
 Bayesian fusion of two points gauss. More...
 
void inverse (CPosePDF &o) const
 Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF. More...
 
void operator+= (const CPose2D &Ap)
 Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated). More...
 
double evaluatePDF (const CPose2D &x) const
 Evaluates the PDF at a given point. More...
 
double evaluateNormalizedPDF (const CPose2D &x) const
 Evaluates the ratio PDF(x) / PDF(MEAN), that is, the normalized PDF in the range [0,1]. More...
 
double mahalanobisDistanceTo (const CPosePDFGaussian &theOther)
 Computes the Mahalanobis distance between the centers of two Gaussians. More...
 
void assureMinCovariance (const double &minStdXY, const double &minStdPhi)
 Substitutes the diagonal elements if (square) they are below some given minimum values (Use this before bayesianFusion, for example, to avoid inversion of singular matrixes, etc...) More...
 
void operator+= (const CPosePDFGaussian &Ap)
 Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated) (see formulas in jacobiansPoseComposition ). More...
 
void operator-= (const CPosePDFGaussian &ref)
 Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition (both the mean, and the covariance matrix are updated) More...
 
void composePoint (const mrpt::math::TPoint2D &l, CPoint2DPDFGaussian &g) const
 Returns the PDF of the 2D point $ g = q \oplus l$ with "q"=this pose and "l" a point without uncertainty. More...
 
template<class OPENGL_SETOFOBJECTSPTR >
void getAs3DObject (OPENGL_SETOFOBJECTSPTR &out_obj) const
 Returns a 3D representation of this PDF (it doesn't clear the current contents of out_obj, but append new OpenGL objects to that list) More...
 
template<class OPENGL_SETOFOBJECTSPTR >
OPENGL_SETOFOBJECTSPTR getAs3DObject () const
 Returns a 3D representation of this PDF. More...
 
mrpt::utils::CObjectPtr duplicateGetSmartPtr () const
 Returns a copy of the object, indepently of its class, as a smart pointer (the newly created object will exist as long as any copy of this smart pointer). More...
 
CObject * clone () const
 Cloning interface for smart pointers. More...
 
virtual void getMean (CPose2D &mean_point) const=0
 Returns the mean, or mathematical expectation of the probability density distribution (PDF). More...
 
virtual void getCovarianceAndMean (CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &cov, CPose2D &mean_point) const=0
 Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...
 
void getCovarianceDynAndMean (CMatrixDouble &cov, CPose2D &mean_point) const
 Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...
 
CPose2D getMeanVal () const
 Returns the mean, or mathematical expectation of the probability density distribution (PDF). More...
 
void getCovariance (CMatrixDouble &cov) const
 Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...
 
void getCovariance (CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &cov) const
 Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...
 
CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > getCovariance () const
 Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...
 
virtual void getInformationMatrix (CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &inf) const
 Returns the information (inverse covariance) matrix (a STATE_LEN x STATE_LEN matrix) Unless reimplemented in derived classes, this method first reads the covariance, then invert it. More...
 
virtual void drawSingleSample (CPose2D &outPart) const=0
 Draws a single sample from the distribution. More...
 
virtual void drawManySamples (size_t N, std::vector< vector_double > &outSamples) const
 Draws a number of samples from the distribution, and saves as a list of 1xSTATE_LEN vectors, where each row contains a (x,y,z,yaw,pitch,roll) datum. More...
 
double getCovarianceEntropy () const
 Compute the entropy of the estimated covariance matrix. More...
 

Static Public Member Functions

static void jacobiansPoseComposition (const CPose2D &x, const CPose2D &u, CMatrixDouble33 &df_dx, CMatrixDouble33 &df_du, const bool compute_df_dx=true, const bool compute_df_du=true)
 This static method computes the pose composition Jacobians, with these formulas: More...
 
static void jacobiansPoseComposition (const CPosePDFGaussian &x, const CPosePDFGaussian &u, CMatrixDouble33 &df_dx, CMatrixDouble33 &df_du)
 
static bool is_3D ()
 
static bool is_PDF ()
 

Public Attributes

Data fields
CPose2D mean
 The mean value. More...
 
CMatrixDouble33 cov
 The 3x3 covariance matrix. More...
 

Static Public Attributes

static const mrpt::utils::TRuntimeClassId classCObject
 
static const size_t state_length
 The length of the variable, for example, 3 for a 3D point, 6 for a 3D pose (x y z yaw pitch roll). More...
 
RTTI stuff
static const mrpt::utils::TRuntimeClassId classCPosePDF
 
RTTI stuff
static const mrpt::utils::TRuntimeClassId classCSerializable
 

Protected Member Functions

void assureSymmetry ()
 Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!) More...
 
CSerializable virtual methods
void writeToStream (mrpt::utils::CStream &out, int *getVersion) const
 Introduces a pure virtual method responsible for writing to a CStream. More...
 
void readFromStream (mrpt::utils::CStream &in, int version)
 Introduces a pure virtual method responsible for loading from a CStream This can not be used directly be users, instead use "stream >> object;" for reading it from a stream or "stream >> object_ptr;" if the class is unknown apriori. More...
 

RTTI stuff

typedef CPosePDFGaussianPtr SmartPtr
 
static mrpt::utils::CLASSINIT _init_CPosePDFGaussian
 
static mrpt::utils::TRuntimeClassId classCPosePDFGaussian
 
static const mrpt::utils::TRuntimeClassIdclassinfo
 
static const mrpt::utils::TRuntimeClassId_GetBaseClass ()
 
virtual const mrpt::utils::TRuntimeClassIdGetRuntimeClass () const
 Returns information about the class of an object in runtime. More...
 
virtual mrpt::utils::CObjectduplicate () const
 Returns a copy of the object, indepently of its class. More...
 
static mrpt::utils::CObjectCreateObject ()
 
static CPosePDFGaussianPtr Create ()
 

Member Typedef Documentation

◆ SmartPtr

A typedef for the associated smart pointer

Definition at line 63 of file CPosePDFGaussian.h.

◆ type_value

The type of the state the PDF represents.

Definition at line 61 of file CProbabilityDensityFunction.h.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum
inherited
Enumerator
is_3D_val 

Definition at line 119 of file CPosePDF.h.

◆ anonymous enum

anonymous enum
inherited
Enumerator
is_PDF_val 

Definition at line 121 of file CPosePDF.h.

Constructor & Destructor Documentation

◆ CPosePDFGaussian() [1/5]

mrpt::poses::CPosePDFGaussian::CPosePDFGaussian ( )

Default constructor.

◆ CPosePDFGaussian() [2/5]

mrpt::poses::CPosePDFGaussian::CPosePDFGaussian ( const CPose2D init_Mean)
explicit

Constructor.

◆ CPosePDFGaussian() [3/5]

mrpt::poses::CPosePDFGaussian::CPosePDFGaussian ( const CPose2D init_Mean,
const CMatrixDouble33 init_Cov 
)

Constructor.

◆ CPosePDFGaussian() [4/5]

mrpt::poses::CPosePDFGaussian::CPosePDFGaussian ( const CPosePDF o)
inlineexplicit

Copy constructor, including transformations between other PDFs.

Definition at line 95 of file CPosePDFGaussian.h.

◆ CPosePDFGaussian() [5/5]

mrpt::poses::CPosePDFGaussian::CPosePDFGaussian ( const CPose3DPDF o)
inlineexplicit

Copy constructor, including transformations between other PDFs.

Definition at line 98 of file CPosePDFGaussian.h.

Member Function Documentation

◆ _GetBaseClass()

static const mrpt::utils::TRuntimeClassId* mrpt::poses::CPosePDFGaussian::_GetBaseClass ( )
staticprotected

◆ assureMinCovariance()

void mrpt::poses::CPosePDFGaussian::assureMinCovariance ( const double &  minStdXY,
const double &  minStdPhi 
)

Substitutes the diagonal elements if (square) they are below some given minimum values (Use this before bayesianFusion, for example, to avoid inversion of singular matrixes, etc...)

◆ assureSymmetry()

void mrpt::poses::CPosePDFGaussian::assureSymmetry ( )
protected

Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!)

◆ bayesianFusion()

void mrpt::poses::CPosePDFGaussian::bayesianFusion ( const CPosePDF p1,
const CPosePDF p2,
const double &  minMahalanobisDistToDrop = 0 
)
virtual

Bayesian fusion of two points gauss.

distributions, then save the result in this object. The process is as follows:

  • (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 = (S1-1 + S2-1)-1; x = S * ( S1-1*x1 + S2-1*x2 );

Implements mrpt::poses::CPosePDF.

◆ changeCoordinatesReference() [1/2]

void mrpt::poses::CPosePDFGaussian::changeCoordinatesReference ( const CPose3D newReferenceBase)
virtual

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.

Implements mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >.

◆ changeCoordinatesReference() [2/2]

void mrpt::poses::CPosePDFGaussian::changeCoordinatesReference ( const CPose2D 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.

◆ clone()

CObject* mrpt::utils::CObject::clone ( ) const
inlineinherited

Cloning interface for smart pointers.

Definition at line 161 of file CObject.h.

◆ composePoint()

void mrpt::poses::CPosePDFGaussian::composePoint ( const mrpt::math::TPoint2D l,
CPoint2DPDFGaussian g 
) const

Returns the PDF of the 2D point $ g = q \oplus l$ with "q"=this pose and "l" a point without uncertainty.

◆ copyFrom() [1/2]

void mrpt::poses::CPosePDFGaussian::copyFrom ( const CPosePDF o)
virtual

Copy operator, translating if necesary (for example, between particles and gaussian representations)

Implements mrpt::poses::CPosePDF.

◆ copyFrom() [2/2]

void mrpt::poses::CPosePDFGaussian::copyFrom ( const CPose3DPDF o)

Copy operator, translating if necesary (for example, between particles and gaussian representations)

◆ Create()

static CPosePDFGaussianPtr mrpt::poses::CPosePDFGaussian::Create ( )
static

◆ CreateObject()

static mrpt::utils::CObject* mrpt::poses::CPosePDFGaussian::CreateObject ( )
static

◆ drawManySamples() [1/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::drawManySamples ( size_t  N,
std::vector< vector_double > &  outSamples 
) const
inlinevirtualinherited

Draws a number of samples from the distribution, and saves as a list of 1xSTATE_LEN vectors, where each row contains a (x,y,z,yaw,pitch,roll) datum.

This base method just call N times to drawSingleSample, but derived classes should implemented optimized method for each particular PDF.

Definition at line 146 of file CProbabilityDensityFunction.h.

◆ drawManySamples() [2/2]

void mrpt::poses::CPosePDFGaussian::drawManySamples ( size_t  N,
std::vector< vector_double > &  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.

◆ drawSingleSample() [1/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::drawSingleSample ( CPose2D outPart) const
pure virtualinherited

Draws a single sample from the distribution.

◆ drawSingleSample() [2/2]

void mrpt::poses::CPosePDFGaussian::drawSingleSample ( CPose2D outPart) const

Draws a single sample from the distribution.

◆ duplicate()

virtual mrpt::utils::CObject* mrpt::poses::CPosePDFGaussian::duplicate ( ) const
virtual

Returns a copy of the object, indepently of its class.

Implements mrpt::utils::CObject.

◆ duplicateGetSmartPtr()

mrpt::utils::CObjectPtr mrpt::utils::CObject::duplicateGetSmartPtr ( ) const
inlineinherited

Returns a copy of the object, indepently of its class, as a smart pointer (the newly created object will exist as long as any copy of this smart pointer).

Definition at line 158 of file CObject.h.

◆ evaluateNormalizedPDF()

double mrpt::poses::CPosePDFGaussian::evaluateNormalizedPDF ( const CPose2D x) const

Evaluates the ratio PDF(x) / PDF(MEAN), that is, the normalized PDF in the range [0,1].

◆ evaluatePDF()

double mrpt::poses::CPosePDFGaussian::evaluatePDF ( const CPose2D x) const

Evaluates the PDF at a given point.

◆ getAs3DObject() [1/2]

template<class OPENGL_SETOFOBJECTSPTR >
void mrpt::poses::CPosePDF::getAs3DObject ( OPENGL_SETOFOBJECTSPTR &  out_obj) const
inlineinherited

Returns a 3D representation of this PDF (it doesn't clear the current contents of out_obj, but append new OpenGL objects to that list)

Note
Needs the mrpt-opengl library, and using mrpt::opengl::CSetOfObjectsPtr as template argument.

Definition at line 128 of file CPosePDF.h.

References mrpt::opengl::posePDF2opengl().

◆ getAs3DObject() [2/2]

template<class OPENGL_SETOFOBJECTSPTR >
OPENGL_SETOFOBJECTSPTR mrpt::poses::CPosePDF::getAs3DObject ( ) const
inlineinherited

Returns a 3D representation of this PDF.

Note
Needs the mrpt-opengl library, and using mrpt::opengl::CSetOfObjectsPtr as template argument.

Definition at line 137 of file CPosePDF.h.

References mrpt::opengl::posePDF2opengl().

◆ getCovariance() [1/3]

void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovariance ( CMatrixDouble cov) const
inlineinherited

Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)

See also
getMean, getCovarianceAndMean, getInformationMatrix

Definition at line 96 of file CProbabilityDensityFunction.h.

References mrpt::math::cov().

◆ getCovariance() [2/3]

void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovariance ( CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &  cov) const
inlineinherited

Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)

See also
getMean, getCovarianceAndMean, getInformationMatrix

Definition at line 105 of file CProbabilityDensityFunction.h.

References mrpt::math::cov().

◆ getCovariance() [3/3]

CMatrixFixedNumeric<double,STATE_LEN,STATE_LEN> mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovariance ( ) const
inlineinherited

Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)

See also
getMean, getInformationMatrix

Definition at line 114 of file CProbabilityDensityFunction.h.

References mrpt::math::cov(), and mrpt::math::UNINITIALIZED_MATRIX.

◆ getCovarianceAndMean() [1/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovarianceAndMean ( CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &  cov,
CPose2D mean_point 
) const
pure virtualinherited

Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.

See also
getMean, getInformationMatrix

◆ getCovarianceAndMean() [2/2]

void mrpt::poses::CPosePDFGaussian::getCovarianceAndMean ( CMatrixDouble33 cov,
CPose2D mean_point 
) const
inline

Returns an estimate of the pose covariance matrix (3x3 cov matrix) and the mean, both at once.

See also
getMean

Definition at line 110 of file CPosePDFGaussian.h.

References mrpt::math::cov(), and mean().

◆ getCovarianceDynAndMean()

void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovarianceDynAndMean ( CMatrixDouble cov,
CPose2D mean_point 
) const
inlineinherited

Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.

See also
getMean, getInformationMatrix

Definition at line 76 of file CProbabilityDensityFunction.h.

References mrpt::math::cov(), and mrpt::math::UNINITIALIZED_MATRIX.

◆ getCovarianceEntropy()

double mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovarianceEntropy ( ) const
inlineinherited

Compute the entropy of the estimated covariance matrix.

See also
http://en.wikipedia.org/wiki/Multivariate_normal_distribution#Entropy

Definition at line 165 of file CProbabilityDensityFunction.h.

References det().

◆ getInformationMatrix()

virtual void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getInformationMatrix ( CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &  inf) const
inlinevirtualinherited

Returns the information (inverse covariance) matrix (a STATE_LEN x STATE_LEN matrix) Unless reimplemented in derived classes, this method first reads the covariance, then invert it.

See also
getMean, getCovarianceAndMean

Definition at line 127 of file CProbabilityDensityFunction.h.

References mrpt::math::cov(), and mrpt::math::UNINITIALIZED_MATRIX.

◆ getMean() [1/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getMean ( CPose2D mean_point) const
pure virtualinherited

Returns the mean, or mathematical expectation of the probability density distribution (PDF).

See also
getCovarianceAndMean, getInformationMatrix

◆ getMean() [2/2]

void mrpt::poses::CPosePDFGaussian::getMean ( CPose2D mean_pose) const
inline

Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF).

See also
getCovariance

Definition at line 103 of file CPosePDFGaussian.h.

References mean().

◆ getMeanVal()

CPose2D mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getMeanVal ( ) const
inlineinherited

Returns the mean, or mathematical expectation of the probability density distribution (PDF).

See also
getCovariance, getInformationMatrix

Definition at line 86 of file CProbabilityDensityFunction.h.

◆ getPoseMean() [1/2]

const CPose2D& mrpt::poses::CPosePDFGaussian::getPoseMean ( ) const
inline

Definition at line 79 of file CPosePDFGaussian.h.

References mean().

◆ getPoseMean() [2/2]

CPose2D& mrpt::poses::CPosePDFGaussian::getPoseMean ( )
inline

Definition at line 80 of file CPosePDFGaussian.h.

References mean().

◆ GetRuntimeClass()

virtual const mrpt::utils::TRuntimeClassId* mrpt::poses::CPosePDFGaussian::GetRuntimeClass ( ) const
virtual

Returns information about the class of an object in runtime.

Reimplemented from mrpt::poses::CPosePDF.

◆ inverse()

void mrpt::poses::CPosePDFGaussian::inverse ( CPosePDF o) const
virtual

Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF.

Implements mrpt::poses::CPosePDF.

◆ inverseComposition() [1/2]

void mrpt::poses::CPosePDFGaussian::inverseComposition ( const CPosePDFGaussian x,
const CPosePDFGaussian ref 
)

Set $ this = x1 \ominus x0 $ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (For 'x0' and 'x1' being independent variables!).

◆ inverseComposition() [2/2]

void mrpt::poses::CPosePDFGaussian::inverseComposition ( const CPosePDFGaussian x1,
const CPosePDFGaussian x0,
const CMatrixDouble33 COV_01 
)

Set $ this = x1 \ominus x0 $ , computing the mean using the "-" operator and the covariances through the corresponding Jacobians (Given the 3x3 cross-covariance matrix of variables x0 and x1).

◆ is_3D()

static bool mrpt::poses::CPosePDF::is_3D ( )
inlinestaticinherited

Definition at line 120 of file CPosePDF.h.

◆ is_PDF()

static bool mrpt::poses::CPosePDF::is_PDF ( )
inlinestaticinherited

Definition at line 122 of file CPosePDF.h.

◆ jacobiansPoseComposition() [1/2]

static void mrpt::poses::CPosePDF::jacobiansPoseComposition ( const CPose2D x,
const CPose2D u,
CMatrixDouble33 df_dx,
CMatrixDouble33 df_du,
const bool  compute_df_dx = true,
const bool  compute_df_du = true 
)
staticinherited

This static method computes the pose composition Jacobians, with these formulas:

df_dx =
[ 1, 0, -sin(phi_x)*x_u-cos(phi_x)*y_u ]
[ 0, 1, cos(phi_x)*x_u-sin(phi_x)*y_u ]
[ 0, 0, 1 ]
df_du =
[ cos(phi_x) , -sin(phi_x) , 0 ]
[ sin(phi_x) , cos(phi_x) , 0 ]
[ 0 , 0 , 1 ]

◆ jacobiansPoseComposition() [2/2]

static void mrpt::poses::CPosePDF::jacobiansPoseComposition ( const CPosePDFGaussian x,
const CPosePDFGaussian u,
CMatrixDouble33 df_dx,
CMatrixDouble33 df_du 
)
staticinherited

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

◆ mahalanobisDistanceTo()

double mrpt::poses::CPosePDFGaussian::mahalanobisDistanceTo ( const CPosePDFGaussian theOther)

Computes the Mahalanobis distance between the centers of two Gaussians.

◆ operator+=() [1/2]

void mrpt::poses::CPosePDFGaussian::operator+= ( const CPose2D Ap)

Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated).

◆ operator+=() [2/2]

void mrpt::poses::CPosePDFGaussian::operator+= ( const CPosePDFGaussian Ap)

Makes: thisPDF = thisPDF + Ap, where "+" is pose composition (both the mean, and the covariance matrix are updated) (see formulas in jacobiansPoseComposition ).

◆ operator-=()

void mrpt::poses::CPosePDFGaussian::operator-= ( const CPosePDFGaussian ref)
inline

Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition (both the mean, and the covariance matrix are updated)

Definition at line 190 of file CPosePDFGaussian.h.

◆ readFromStream()

void mrpt::poses::CPosePDFGaussian::readFromStream ( mrpt::utils::CStream in,
int  version 
)
protectedvirtual

Introduces a pure virtual method responsible for loading from a CStream This can not be used directly be users, instead use "stream >> object;" for reading it from a stream or "stream >> object_ptr;" if the class is unknown apriori.

Parameters
inThe input binary stream where the object data must read from.
versionThe version of the object stored in the stream: use this version number in your code to know how to read the incoming data.
Exceptions
std::exceptionOn any error, see CStream::ReadBuffer
See also
CStream

Implements mrpt::utils::CSerializable.

◆ rotateCov()

void mrpt::poses::CPosePDFGaussian::rotateCov ( const double  ang)

Rotate the covariance matrix by replacing it by $ \mathbf{R}~\mathbf{COV}~\mathbf{R}^t $, where $ \mathbf{R} = \left[ \begin{array}{ccc} \cos\alpha & -\sin\alpha & 0 \\ \sin\alpha & \cos\alpha & 0 \\ 0 & 0 & 1 \end{array}\right] $.

◆ saveToTextFile()

void mrpt::poses::CPosePDFGaussian::saveToTextFile ( const std::string &  file) const
virtual

Save PDF's particles to a text file, containing the 2D pose in the first line, then the covariance matrix in next 3 lines.

Implements mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >.

◆ writeToStream()

void mrpt::poses::CPosePDFGaussian::writeToStream ( mrpt::utils::CStream out,
int *  getVersion 
) const
protectedvirtual

Introduces a pure virtual method responsible for writing to a CStream.

This can not be used directly be users, instead use "stream << object;" for writing it to a stream.

Parameters
outThe output binary stream where object must be dumped.
getVersionIf NULL, the object must be dumped. If not, only the version of the object dump must be returned in this pointer. This enables the versioning of objects dumping and backward compatibility with previously stored data.
Exceptions
std::exceptionOn any error, see CStream::WriteBuffer
See also
CStream

Implements mrpt::utils::CSerializable.

Member Data Documentation

◆ _init_CPosePDFGaussian

mrpt::utils::CLASSINIT mrpt::poses::CPosePDFGaussian::_init_CPosePDFGaussian
staticprotected

Definition at line 63 of file CPosePDFGaussian.h.

◆ classCObject

const mrpt::utils::TRuntimeClassId mrpt::utils::CObject::classCObject
staticinherited

Definition at line 146 of file CObject.h.

◆ classCPosePDF

const mrpt::utils::TRuntimeClassId mrpt::poses::CPosePDF::classCPosePDF
staticinherited

Definition at line 69 of file CPosePDF.h.

◆ classCPosePDFGaussian

mrpt::utils::TRuntimeClassId mrpt::poses::CPosePDFGaussian::classCPosePDFGaussian
static

Definition at line 63 of file CPosePDFGaussian.h.

◆ classCSerializable

const mrpt::utils::TRuntimeClassId mrpt::utils::CSerializable::classCSerializable
staticinherited

Definition at line 61 of file CSerializable.h.

◆ classinfo

const mrpt::utils::TRuntimeClassId* mrpt::poses::CPosePDFGaussian::classinfo
static

Definition at line 63 of file CPosePDFGaussian.h.

◆ cov

CMatrixDouble33 mrpt::poses::CPosePDFGaussian::cov

The 3x3 covariance matrix.

Definition at line 75 of file CPosePDFGaussian.h.

Referenced by mrpt::graphs::detail::graph_ops< graph_t >::auxMaha2Dist().

◆ mean

CPose2D mrpt::poses::CPosePDFGaussian::mean

The mean value.

Definition at line 74 of file CPosePDFGaussian.h.

◆ state_length

const size_t mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::state_length
staticinherited

The length of the variable, for example, 3 for a 3D point, 6 for a 3D pose (x y z yaw pitch roll).

Definition at line 60 of file CProbabilityDensityFunction.h.




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