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mrpt::poses::CPosePDFGaussianInf Class Referenceabstract

Detailed Description

A Probability Density function (PDF) of a 2D pose $ p(\mathbf{x}) = [x ~ y ~ \phi ]^t $ as a Gaussian with a mean and the inverse of the covariance.

This class implements a PDF as a mono-modal Gaussian distribution in its information form, that is, keeping the inverse of the covariance matrix instead of the covariance matrix itself.

This class is the dual of CPosePDFGaussian.

See also
CPose2D, CPosePDF, CPosePDFParticles

Definition at line 34 of file CPosePDFGaussianInf.h.

#include <mrpt/poses/CPosePDFGaussianInf.h>

Inheritance diagram for mrpt::poses::CPosePDFGaussianInf:
Inheritance graph

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 ()
 
 CPosePDFGaussianInf ()
 Default constructor (mean=all zeros, inverse covariance=all zeros -> so be careful!) More...
 
 CPosePDFGaussianInf (const CPose2D &init_Mean)
 Constructor with a mean value (inverse covariance=all zeros -> so be careful!) More...
 
 CPosePDFGaussianInf (const CPose2D &init_Mean, const mrpt::math::CMatrixDouble33 &init_CovInv)
 Constructor. More...
 
 CPosePDFGaussianInf (const CPosePDF &o)
 Copy constructor, including transformations between other PDFs. More...
 
 CPosePDFGaussianInf (const CPose3DPDF &o)
 Copy constructor, including transformations between other PDFs. More...
 
void getMean (CPose2D &mean_pose) const MRPT_OVERRIDE
 Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF). More...
 
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. More...
 
virtual void getInformationMatrix (mrpt::math::CMatrixDouble33 &inf) const MRPT_OVERRIDE
 Returns the information (inverse covariance) matrix (a STATE_LEN x STATE_LEN matrix) More...
 
void copyFrom (const CPosePDF &o) MRPT_OVERRIDE
 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 MRPT_OVERRIDE
 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) MRPT_OVERRIDE
 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 CPosePDFGaussianInf &x, const CPosePDFGaussianInf &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 CPosePDFGaussianInf &x1, const CPosePDFGaussianInf &x0, const mrpt::math::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 MRPT_OVERRIDE
 Draws a single sample from the distribution. More...
 
void drawManySamples (size_t N, std::vector< mrpt::math::CVectorDouble > &outSamples) const MRPT_OVERRIDE
 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) MRPT_OVERRIDE
 Bayesian fusion of two points gauss. More...
 
void inverse (CPosePDF &o) const MRPT_OVERRIDE
 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 CPosePDFGaussianInf &theOther)
 Computes the Mahalanobis distance between the centers of two Gaussians. More...
 
void operator+= (const CPosePDFGaussianInf &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 CPosePDFGaussianInf &ref)
 Makes: thisPDF = thisPDF - Ap, where "-" is pose inverse composition (both the mean, and the covariance matrix are updated) 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...
 
virtual void getMean (CPose2D &mean_point) const=0
 Returns the mean, or mathematical expectation of the probability density distribution (PDF). More...
 
virtual void getCovarianceAndMean (mrpt::math::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 (mrpt::math::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 (mrpt::math::CMatrixDouble &cov) const
 Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...
 
void getCovariance (mrpt::math::CMatrixFixedNumeric< double, STATE_LEN, STATE_LEN > &cov) const
 Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...
 
mrpt::math::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 (mrpt::math::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...
 
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, mrpt::math::CMatrixDouble33 &df_dx, mrpt::math::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, mrpt::math::CMatrixDouble33 &df_dx, mrpt::math::CMatrixDouble33 &df_du)
 This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts. More...
 
static bool is_3D ()
 
static bool is_PDF ()
 

Public Attributes

Data fields
CPose2D mean
 The mean value. More...
 
mrpt::math::CMatrixDouble33 cov_inv
 The inverse of the 3x3 covariance matrix (the "information" matrix) More...
 

Static Public Attributes

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 <br>
static const mrpt::utils::TRuntimeClassId classCPosePDF
 

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 MRPT_OVERRIDE
 
void readFromStream (mrpt::utils::CStream &in, int version) MRPT_OVERRIDE
 

RTTI stuff <br>

typedef CPosePDFGaussianInfPtr SmartPtr
 
static mrpt::utils::CLASSINIT _init_CPosePDFGaussianInf
 
static mrpt::utils::TRuntimeClassId classCPosePDFGaussianInf
 
static const mrpt::utils::TRuntimeClassIdclassinfo
 
static const mrpt::utils::TRuntimeClassId_GetBaseClass ()
 
virtual const mrpt::utils::TRuntimeClassIdGetRuntimeClass () const MRPT_OVERRIDE
 
virtual mrpt::utils::CObjectduplicate () const MRPT_OVERRIDE
 
static mrpt::utils::CObjectCreateObject ()
 
static CPosePDFGaussianInfPtr Create ()
 

Member Typedef Documentation

◆ SmartPtr

A typedef for the associated smart pointer

Definition at line 37 of file CPosePDFGaussianInf.h.

◆ type_value

typedef CPose2D mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::type_value
inherited

The type of the state the PDF represents.

Definition at line 32 of file CProbabilityDensityFunction.h.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum
inherited
Enumerator
is_3D_val 

Definition at line 91 of file CPosePDF.h.

◆ anonymous enum

anonymous enum
inherited
Enumerator
is_PDF_val 

Definition at line 93 of file CPosePDF.h.

Constructor & Destructor Documentation

◆ CPosePDFGaussianInf() [1/5]

mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf ( )

Default constructor (mean=all zeros, inverse covariance=all zeros -> so be careful!)

◆ CPosePDFGaussianInf() [2/5]

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

Constructor with a mean value (inverse covariance=all zeros -> so be careful!)

◆ CPosePDFGaussianInf() [3/5]

mrpt::poses::CPosePDFGaussianInf::CPosePDFGaussianInf ( const CPose2D init_Mean,
const mrpt::math::CMatrixDouble33 init_CovInv 
)

Constructor.

◆ CPosePDFGaussianInf() [4/5]

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

Copy constructor, including transformations between other PDFs.

Definition at line 66 of file CPosePDFGaussianInf.h.

◆ CPosePDFGaussianInf() [5/5]

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

Copy constructor, including transformations between other PDFs.

Definition at line 69 of file CPosePDFGaussianInf.h.

Member Function Documentation

◆ _GetBaseClass()

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

◆ assureSymmetry()

void mrpt::poses::CPosePDFGaussianInf::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::CPosePDFGaussianInf::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::CPosePDFGaussianInf::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.

◆ changeCoordinatesReference() [2/2]

void mrpt::poses::CPosePDFGaussianInf::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 >.

◆ copyFrom() [1/2]

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

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

◆ copyFrom() [2/2]

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

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

Implements mrpt::poses::CPosePDF.

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

◆ Create()

static CPosePDFGaussianInfPtr mrpt::poses::CPosePDFGaussianInf::Create ( )
static

◆ CreateObject()

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

◆ drawManySamples()

void mrpt::poses::CPosePDFGaussianInf::drawManySamples ( size_t  N,
std::vector< mrpt::math::CVectorDouble > &  outSamples 
) const
virtual

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.

Reimplemented from mrpt::utils::CProbabilityDensityFunction< CPose2D, 3 >.

◆ drawSingleSample() [1/2]

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

Draws a single sample from the distribution.

◆ drawSingleSample() [2/2]

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

Draws a single sample from the distribution.

◆ duplicate()

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

◆ evaluateNormalizedPDF()

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

Evaluates the PDF at a given point.

◆ getAs3DObject() [1/2]

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 109 of file CPosePDF.h.

◆ getAs3DObject() [2/2]

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 100 of file CPosePDF.h.

◆ getCovariance() [1/3]

mrpt::math::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 85 of file CProbabilityDensityFunction.h.

◆ getCovariance() [2/3]

void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovariance ( mrpt::math::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 67 of file CProbabilityDensityFunction.h.

◆ getCovariance() [3/3]

void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovariance ( mrpt::math::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 76 of file CProbabilityDensityFunction.h.

◆ getCovarianceAndMean() [1/2]

void mrpt::poses::CPosePDFGaussianInf::getCovarianceAndMean ( mrpt::math::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 79 of file CPosePDFGaussianInf.h.

References mean().

◆ getCovarianceAndMean() [2/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovarianceAndMean ( mrpt::math::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

◆ getCovarianceDynAndMean()

void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovarianceDynAndMean ( mrpt::math::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 47 of file CProbabilityDensityFunction.h.

◆ 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 136 of file CProbabilityDensityFunction.h.

◆ getInformationMatrix() [1/2]

virtual void mrpt::poses::CPosePDFGaussianInf::getInformationMatrix ( mrpt::math::CMatrixDouble33 inf) const
inlinevirtual

Returns the information (inverse covariance) matrix (a STATE_LEN x STATE_LEN matrix)

See also
getMean, getCovarianceAndMean

Definition at line 85 of file CPosePDFGaussianInf.h.

◆ getInformationMatrix() [2/2]

virtual void mrpt::utils::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getInformationMatrix ( mrpt::math::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 98 of file CProbabilityDensityFunction.h.

◆ 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::CPosePDFGaussianInf::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 73 of file CPosePDFGaussianInf.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 57 of file CProbabilityDensityFunction.h.

◆ getPoseMean() [1/2]

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

Definition at line 54 of file CPosePDFGaussianInf.h.

References mean().

◆ getPoseMean() [2/2]

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

Definition at line 53 of file CPosePDFGaussianInf.h.

References mean().

◆ GetRuntimeClass()

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

Reimplemented from mrpt::poses::CPosePDF.

◆ inverse()

void mrpt::poses::CPosePDFGaussianInf::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::CPosePDFGaussianInf::inverseComposition ( const CPosePDFGaussianInf x,
const CPosePDFGaussianInf 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::CPosePDFGaussianInf::inverseComposition ( const CPosePDFGaussianInf x1,
const CPosePDFGaussianInf x0,
const mrpt::math::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 92 of file CPosePDF.h.

◆ is_PDF()

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

Definition at line 94 of file CPosePDF.h.

◆ jacobiansPoseComposition() [1/2]

static void mrpt::poses::CPosePDF::jacobiansPoseComposition ( const CPose2D x,
const CPose2D u,
mrpt::math::CMatrixDouble33 df_dx,
mrpt::math::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 ]

Referenced by mrpt::math::jacobians::jacobs_2D_pose_comp().

◆ jacobiansPoseComposition() [2/2]

static void mrpt::poses::CPosePDF::jacobiansPoseComposition ( const CPosePDFGaussian x,
const CPosePDFGaussian u,
mrpt::math::CMatrixDouble33 df_dx,
mrpt::math::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::CPosePDFGaussianInf::mahalanobisDistanceTo ( const CPosePDFGaussianInf theOther)

Computes the Mahalanobis distance between the centers of two Gaussians.

◆ operator+=() [1/2]

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

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

Definition at line 153 of file CPosePDFGaussianInf.h.

◆ readFromStream()

void mrpt::poses::CPosePDFGaussianInf::readFromStream ( mrpt::utils::CStream in,
int  version 
)
protected

◆ rotateCov()

void mrpt::poses::CPosePDFGaussianInf::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::CPosePDFGaussianInf::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::CPosePDFGaussianInf::writeToStream ( mrpt::utils::CStream out,
int *  getVersion 
) const
protected

Member Data Documentation

◆ _init_CPosePDFGaussianInf

mrpt::utils::CLASSINIT mrpt::poses::CPosePDFGaussianInf::_init_CPosePDFGaussianInf
staticprotected

Definition at line 37 of file CPosePDFGaussianInf.h.

◆ classCPosePDF

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

Definition at line 41 of file CPosePDF.h.

◆ classCPosePDFGaussianInf

mrpt::utils::TRuntimeClassId mrpt::poses::CPosePDFGaussianInf::classCPosePDFGaussianInf
static

Definition at line 37 of file CPosePDFGaussianInf.h.

◆ classinfo

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

Definition at line 37 of file CPosePDFGaussianInf.h.

◆ cov_inv

mrpt::math::CMatrixDouble33 mrpt::poses::CPosePDFGaussianInf::cov_inv

The inverse of the 3x3 covariance matrix (the "information" matrix)

Definition at line 49 of file CPosePDFGaussianInf.h.

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

◆ mean

CPose2D mrpt::poses::CPosePDFGaussianInf::mean

◆ 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 31 of file CProbabilityDensityFunction.h.




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