MRPT  1.9.9
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
Examples:
serialization_json_example/test.cpp.

Definition at line 28 of file CPosePDFGaussian.h.

#include <mrpt/poses/CPosePDFGaussian.h>

Inheritance diagram for mrpt::poses::CPosePDFGaussian:

Public Types

enum  { is_3D_val = 0 }
 
enum  { is_PDF_val = 1 }
 
using type_value = CPose2D
 The type of the state the PDF represents. More...
 
using self_t = CProbabilityDensityFunction< CPose2D, STATE_LEN >
 
using cov_mat_t = mrpt::math::CMatrixFixed< double, STATE_LEN, STATE_LEN >
 Covariance matrix type. More...
 
using inf_mat_t = cov_mat_t
 Information matrix type. 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 mrpt::math::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 override
 
std::tuple< cov_mat_t, type_valuegetCovarianceAndMean () const override
 Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...
 
void copyFrom (const CPosePDF &o) 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...
 
bool saveToTextFile (const std::string &file) const 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) 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 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 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 override
 Draws a single sample from the distribution. More...
 
void drawManySamples (size_t N, std::vector< mrpt::math::CVectorDouble > &outSamples) const 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) override
 Bayesian fusion of two points gauss. More...
 
void inverse (CPosePDF &o) const 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 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...
 
virtual mxArraywriteToMatlab () const
 Introduces a pure virtual method responsible for writing to a mxArray Matlab object, typically a MATLAB struct whose contents are documented in each derived class. More...
 
virtual void getMean (type_value &mean_point) const=0
 Returns the mean, or mathematical expectation of the probability density distribution (PDF). More...
 
virtual void getCovarianceAndMean (cov_mat_t &c, CPose2D &mean) const final
 
void getCovarianceDynAndMean (mrpt::math::CMatrixDouble &cov, type_value &mean_point) const
 Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once. More...
 
type_value 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 (cov_mat_t &cov) const
 Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...
 
cov_mat_t getCovariance () const
 Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix) More...
 
virtual bool isInfType () const
 Returns whether the class instance holds the uncertainty in covariance or information form. More...
 
virtual void getInformationMatrix (inf_mat_t &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...
 
RTTI classes and functions for polymorphic hierarchies
mrpt::rtti::CObject::Ptr duplicateGetSmartPtr () const
 Makes a deep copy of the object and returns a smart pointer to it. 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)
 
static constexpr bool is_3D ()
 
static constexpr bool is_PDF ()
 

Public Attributes

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

Static Public Attributes

static constexpr 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...
 

Protected Member Functions

void enforceCovSymmetry ()
 Assures the symmetry of the covariance matrix (eventually certain operations in the math-coprocessor lead to non-symmetric matrixes!) More...
 
CSerializable virtual methods
uint8_t serializeGetVersion () const override
 Must return the current versioning number of the object. More...
 
void serializeTo (mrpt::serialization::CArchive &out) const override
 Pure virtual method for writing (serializing) to an abstract archive. More...
 
void serializeFrom (mrpt::serialization::CArchive &in, uint8_t serial_version) override
 Pure virtual method for reading (deserializing) from an abstract archive. More...
 
CSerializable virtual methods
virtual void serializeTo (CSchemeArchiveBase &out) const
 Virtual method for writing (serializing) to an abstract schema based archive. More...
 
virtual void serializeFrom (CSchemeArchiveBase &in)
 Virtual method for reading (deserializing) from an abstract schema based archive. More...
 

RTTI stuff

using Ptr = std::shared_ptr< CPosePDFGaussian >
 
using ConstPtr = std::shared_ptr< const CPosePDFGaussian >
 
using UniquePtr = std::unique_ptr< CPosePDFGaussian >
 
using ConstUniquePtr = std::unique_ptr< const CPosePDFGaussian >
 
static mrpt::rtti::CLASSINIT _init_CPosePDFGaussian
 
static const mrpt::rtti::TRuntimeClassId runtimeClassId
 
static constexpr const char * className = "CPosePDFGaussian"
 
static const mrpt::rtti::TRuntimeClassId_GetBaseClass ()
 
static constexpr auto getClassName ()
 
static const mrpt::rtti::TRuntimeClassIdGetRuntimeClassIdStatic ()
 
static std::shared_ptr< CObjectCreateObject ()
 
template<typename... Args>
static Ptr Create (Args &&... args)
 
template<typename Alloc , typename... Args>
static Ptr CreateAlloc (const Alloc &alloc, Args &&... args)
 
template<typename... Args>
static UniquePtr CreateUnique (Args &&... args)
 
virtual const mrpt::rtti::TRuntimeClassIdGetRuntimeClass () const override
 Returns information about the class of an object in runtime. More...
 
virtual mrpt::rtti::CObjectclone () const override
 Returns a deep copy (clone) of the object, indepently of its class. More...
 

Member Typedef Documentation

◆ ConstPtr

◆ ConstUniquePtr

Definition at line 30 of file CPosePDFGaussian.h.

◆ cov_mat_t

using mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::cov_mat_t = mrpt::math::CMatrixFixed<double, STATE_LEN, STATE_LEN>
inherited

Covariance matrix type.

Definition at line 37 of file CProbabilityDensityFunction.h.

◆ inf_mat_t

Information matrix type.

Definition at line 39 of file CProbabilityDensityFunction.h.

◆ Ptr

A type for the associated smart pointer

Definition at line 30 of file CPosePDFGaussian.h.

◆ self_t

using mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::self_t = CProbabilityDensityFunction<CPose2D , STATE_LEN>
inherited

Definition at line 35 of file CProbabilityDensityFunction.h.

◆ type_value

The type of the state the PDF represents.

Definition at line 34 of file CProbabilityDensityFunction.h.

◆ UniquePtr

Definition at line 30 of file CPosePDFGaussian.h.

Member Enumeration Documentation

◆ anonymous enum

anonymous enum
inherited
Enumerator
is_3D_val 

Definition at line 94 of file CPosePDF.h.

◆ anonymous enum

anonymous enum
inherited
Enumerator
is_PDF_val 

Definition at line 99 of file CPosePDF.h.

Constructor & Destructor Documentation

◆ CPosePDFGaussian() [1/5]

CPosePDFGaussian::CPosePDFGaussian ( )

Default constructor.

Definition at line 38 of file CPosePDFGaussian.cpp.

◆ CPosePDFGaussian() [2/5]

CPosePDFGaussian::CPosePDFGaussian ( const CPose2D init_Mean)
explicit

Constructor.

Definition at line 51 of file CPosePDFGaussian.cpp.

References cov, and mrpt::math::MatrixVectorBase< Scalar, Derived >::setZero().

Here is the call graph for this function:

◆ CPosePDFGaussian() [3/5]

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

Constructor.

Definition at line 42 of file CPosePDFGaussian.cpp.

◆ CPosePDFGaussian() [4/5]

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

Copy constructor, including transformations between other PDFs.

Definition at line 66 of file CPosePDFGaussian.h.

References copyFrom().

Here is the call graph for this function:

◆ CPosePDFGaussian() [5/5]

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

Copy constructor, including transformations between other PDFs.

Definition at line 68 of file CPosePDFGaussian.h.

References copyFrom().

Here is the call graph for this function:

Member Function Documentation

◆ _GetBaseClass()

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

◆ assureMinCovariance()

void 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...)

Definition at line 419 of file CPosePDFGaussian.cpp.

References cov, and mrpt::square().

Here is the call graph for this function:

◆ bayesianFusion()

void CPosePDFGaussian::bayesianFusion ( const CPosePDF p1,
const CPosePDF p2,
const double  minMahalanobisDistToDrop = 0 
)
overridevirtual

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.

Definition at line 259 of file CPosePDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), ASSERT_, CLASS_ID, cov, enforceCovSymmetry(), mrpt::poses::CPosePDF::GetRuntimeClass(), mrpt::math::MatrixBase< Scalar, Derived >::inverse_LLt(), mean, MRPT_END, MRPT_START, MRPT_UNUSED_PARAM, mrpt::poses::CPose2D::normalizePhi(), mrpt::poses::CPose2D::phi(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Referenced by mrpt::poses::CPosePDFSOG::bayesianFusion().

Here is the call graph for this function:
Here is the caller graph for this function:

◆ changeCoordinatesReference() [1/2]

void CPosePDFGaussian::changeCoordinatesReference ( const CPose3D newReferenceBase)
overridevirtual

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::poses::CPosePDF.

Definition at line 171 of file CPosePDFGaussian.cpp.

References mrpt::poses::CPose2D::composeFrom(), mean, mrpt::poses::CPose2D::phi(), and rotateCov().

Referenced by operator+().

Here is the call graph for this function:
Here is the caller graph for this function:

◆ changeCoordinatesReference() [2/2]

void 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.

Definition at line 186 of file CPosePDFGaussian.cpp.

References mrpt::poses::CPose2D::composeFrom(), mean, mrpt::poses::CPose2D::phi(), and rotateCov().

Here is the call graph for this function:

◆ clone()

virtual mrpt::rtti::CObject* mrpt::poses::CPosePDFGaussian::clone ( ) const
overridevirtual

Returns a deep copy (clone) of the object, indepently of its class.

Implements mrpt::rtti::CObject.

◆ composePoint()

void 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.

Definition at line 545 of file CPosePDFGaussian.cpp.

References mrpt::poses::CPose2D::composePoint(), cov, mrpt::poses::CPosePDF::jacobiansPoseComposition(), mean, mrpt::math::MatrixVectorBase< Scalar, Derived >::transpose(), mrpt::math::UNINITIALIZED_MATRIX, mrpt::math::TPoint2D_data::x, and mrpt::math::TPoint2D_data::y.

Referenced by mrpt::tfest::se2_l2_robust().

Here is the call graph for this function:
Here is the caller graph for this function:

◆ copyFrom() [1/2]

void CPosePDFGaussian::copyFrom ( const CPosePDF o)
overridevirtual

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

Implements mrpt::poses::CPosePDF.

Definition at line 124 of file CPosePDFGaussian.cpp.

References cov, mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovariance(), mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getMean(), and mean.

Referenced by CPosePDFGaussian(), mrpt::poses::CPoseRandomSampler::getOriginalPDFCov2D(), mrpt::slam::CRangeBearingKFSLAM::OnTransitionNoise(), mrpt::maps::CMultiMetricMapPDF::prediction_and_update_pfOptimalProposal(), mrpt::hmtslam::CLSLAM_RBPF_2DLASER::prediction_and_update_pfOptimalProposal(), and mrpt::slam::CMetricMapBuilderICP::processObservation().

Here is the call graph for this function:
Here is the caller graph for this function:

◆ copyFrom() [2/2]

void CPosePDFGaussian::copyFrom ( const CPose3DPDF o)

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

Definition at line 136 of file CPosePDFGaussian.cpp.

References mrpt::math::MatrixVectorBase< Scalar, Derived >::block(), cov, mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovariance(), mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getMeanVal(), and mean.

Here is the call graph for this function:

◆ Create()

template<typename... Args>
static Ptr mrpt::poses::CPosePDFGaussian::Create ( Args &&...  args)
inlinestatic

Definition at line 30 of file CPosePDFGaussian.h.

◆ CreateAlloc()

template<typename Alloc , typename... Args>
static Ptr mrpt::poses::CPosePDFGaussian::CreateAlloc ( const Alloc &  alloc,
Args &&...  args 
)
inlinestatic

Definition at line 30 of file CPosePDFGaussian.h.

◆ CreateObject()

static std::shared_ptr<CObject> mrpt::poses::CPosePDFGaussian::CreateObject ( )
static

◆ CreateUnique()

template<typename... Args>
static UniquePtr mrpt::poses::CPosePDFGaussian::CreateUnique ( Args &&...  args)
inlinestatic

Definition at line 30 of file CPosePDFGaussian.h.

◆ drawManySamples()

void CPosePDFGaussian::drawManySamples ( size_t  N,
std::vector< mrpt::math::CVectorDouble > &  outSamples 
) const
overridevirtual

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::math::CProbabilityDensityFunction< CPose2D, 3 >.

Definition at line 234 of file CPosePDFGaussian.cpp.

References cov, mrpt::random::CRandomGenerator::drawGaussianMultivariateMany(), mrpt::random::getRandomGenerator(), mean, MRPT_END, MRPT_START, mrpt::poses::CPose2D::phi(), mrpt::math::wrapToPiInPlace(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Here is the call graph for this function:

◆ drawSingleSample() [1/2]

void CPosePDFGaussian::drawSingleSample ( CPose2D outPart) const
override

◆ drawSingleSample() [2/2]

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

Draws a single sample from the distribution.

◆ duplicateGetSmartPtr()

mrpt::rtti::CObject::Ptr CObject::duplicateGetSmartPtr ( ) const
inlineinherited

Makes a deep copy of the object and returns a smart pointer to it.

Definition at line 200 of file CObject.h.

References mrpt::rtti::CObject::clone().

Referenced by mrpt::obs::CRawlog::addActions(), and mrpt::obs::CRawlog::addObservations().

Here is the call graph for this function:
Here is the caller graph for this function:

◆ enforceCovSymmetry()

void CPosePDFGaussian::enforceCovSymmetry ( )
protected

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

Definition at line 357 of file CPosePDFGaussian.cpp.

References cov.

Referenced by bayesianFusion().

Here is the caller graph for this function:

◆ evaluateNormalizedPDF()

double CPosePDFGaussian::evaluateNormalizedPDF ( const CPose2D x) const

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

Definition at line 345 of file CPosePDFGaussian.cpp.

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

Here is the call graph for this function:

◆ evaluatePDF()

double CPosePDFGaussian::evaluatePDF ( const CPose2D x) const

Evaluates the PDF at a given point.

Definition at line 334 of file CPosePDFGaussian.cpp.

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

Here is the call graph for this function:

◆ 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::CSetOfObjects::Ptr as template argument.
By default, ellipsoids for the confidence intervals of "q=3" are drawn; for more mathematical details, see CGeneralizedEllipsoidTemplate::setQuantiles()

Definition at line 113 of file CPosePDF.h.

References mrpt::opengl::posePDF2opengl().

Here is the call graph for this function:

◆ 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::CSetOfObjects::Ptr as template argument.

Definition at line 124 of file CPosePDF.h.

References mrpt::opengl::posePDF2opengl().

Here is the call graph for this function:

◆ getClassName()

static constexpr auto mrpt::poses::CPosePDFGaussian::getClassName ( )
inlinestatic

Definition at line 30 of file CPosePDFGaussian.h.

◆ getCovariance() [1/3]

void mrpt::math::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 88 of file CProbabilityDensityFunction.h.

References mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceDynAndMean().

◆ getCovariance() [2/3]

void mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovariance ( cov_mat_t 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 98 of file CProbabilityDensityFunction.h.

References mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceAndMean().

◆ getCovariance() [3/3]

cov_mat_t mrpt::math::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 108 of file CProbabilityDensityFunction.h.

References mrpt::math::cov(), mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceAndMean(), and mrpt::math::UNINITIALIZED_MATRIX.

◆ getCovarianceAndMean() [1/2]

virtual void mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovarianceAndMean ( cov_mat_t c,
CPose2D &  mean 
) const
inlinefinalvirtualinherited

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

Definition at line 54 of file CProbabilityDensityFunction.h.

References mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceAndMean(), and mrpt::math::mean().

◆ getCovarianceAndMean() [2/2]

std::tuple<cov_mat_t, type_value> mrpt::poses::CPosePDFGaussian::getCovarianceAndMean ( ) const
inlineoverridevirtual

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

See also
getMean, getInformationMatrix

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

Definition at line 72 of file CPosePDFGaussian.h.

References cov, and mean.

◆ getCovarianceDynAndMean()

void mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getCovarianceDynAndMean ( mrpt::math::CMatrixDouble cov,
type_value 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 65 of file CProbabilityDensityFunction.h.

References mrpt::math::cov(), mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovarianceAndMean(), and mrpt::math::UNINITIALIZED_MATRIX.

◆ getCovarianceEntropy()

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

◆ getInformationMatrix()

virtual void mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getInformationMatrix ( inf_mat_t 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 130 of file CProbabilityDensityFunction.h.

References mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getCovariance(), and mrpt::math::MatrixBase< Scalar, Derived >::inverse_LLt().

◆ getMean() [1/2]

virtual void mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::getMean ( type_value 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
inlineoverride

Definition at line 70 of file CPosePDFGaussian.h.

References mean.

◆ getMeanVal()

type_value mrpt::math::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 77 of file CProbabilityDensityFunction.h.

References mrpt::math::CProbabilityDensityFunction< TDATA, STATE_LEN >::getMean().

◆ getPoseMean() [1/2]

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

Definition at line 50 of file CPosePDFGaussian.h.

References mean.

◆ getPoseMean() [2/2]

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

Definition at line 51 of file CPosePDFGaussian.h.

References mean.

◆ GetRuntimeClass()

virtual const mrpt::rtti::TRuntimeClassId* mrpt::poses::CPosePDFGaussian::GetRuntimeClass ( ) const
overridevirtual

Returns information about the class of an object in runtime.

Reimplemented from mrpt::poses::CPosePDF.

◆ GetRuntimeClassIdStatic()

static const mrpt::rtti::TRuntimeClassId& mrpt::poses::CPosePDFGaussian::GetRuntimeClassIdStatic ( )
static

◆ inverse()

void CPosePDFGaussian::inverse ( CPosePDF o) const
overridevirtual

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

Implements mrpt::poses::CPosePDF.

Definition at line 299 of file CPosePDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), ASSERT_, CLASS_ID, cov, mrpt::poses::CPosePDF::GetRuntimeClass(), mean, mrpt::poses::CPose2D::phi(), mrpt::math::MatrixVectorBase< Scalar, Derived >::transpose(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Referenced by PosePDFGaussTests::testPoseInverse().

Here is the call graph for this function:
Here is the caller graph for this function:

◆ inverseComposition() [1/2]

void 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!).

Definition at line 432 of file CPosePDFGaussian.cpp.

References cov, mean, mrpt::math::multiply_HCHt(), mrpt::poses::CPose2D::phi(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Referenced by mrpt::poses::CPosePDFGaussianInf::inverseComposition(), and operator-=().

Here is the call graph for this function:
Here is the caller graph for this function:

◆ inverseComposition() [2/2]

void CPosePDFGaussian::inverseComposition ( const CPosePDFGaussian x1,
const CPosePDFGaussian 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).

Definition at line 477 of file CPosePDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), cov, mean, mrpt::math::multiply_HCHt(), mrpt::poses::CPose2D::phi(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Here is the call graph for this function:

◆ is_3D()

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

Definition at line 98 of file CPosePDF.h.

References mrpt::poses::CPosePDF::is_3D_val.

◆ is_PDF()

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

Definition at line 103 of file CPosePDF.h.

References mrpt::poses::CPosePDF::is_PDF_val.

◆ isInfType()

virtual bool mrpt::math::CProbabilityDensityFunction< CPose2D , STATE_LEN >::isInfType ( ) const
inlinevirtualinherited

Returns whether the class instance holds the uncertainty in covariance or information form.

Note
By default this is going to be covariance form. *Inf classes (e.g. CPosePDFGaussianInf) store it in information form.
See also
mrpt::traits::is_inf_type

Reimplemented in mrpt::poses::CPosePDFGaussianInf.

Definition at line 123 of file CProbabilityDensityFunction.h.

◆ jacobiansPoseComposition() [1/2]

void 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 ]

Definition at line 32 of file CPosePDF.cpp.

References mrpt::math::MatrixBase< Scalar, Derived >::setIdentity(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Referenced by composePoint(), mrpt::poses::CPosePDF::jacobiansPoseComposition(), operator+=(), and mrpt::poses::CPosePDFGaussianInf::operator+=().

Here is the call graph for this function:
Here is the caller graph for this function:

◆ jacobiansPoseComposition() [2/2]

void 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.

Definition at line 22 of file CPosePDF.cpp.

References mrpt::poses::CPosePDF::jacobiansPoseComposition().

Here is the call graph for this function:

◆ mahalanobisDistanceTo()

double CPosePDFGaussian::mahalanobisDistanceTo ( const CPosePDFGaussian theOther)

Computes the Mahalanobis distance between the centers of two Gaussians.

Definition at line 369 of file CPosePDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), cov, mrpt::math::MatrixBase< Scalar, Derived >::inverse_LLt(), mean, MRPT_END, MRPT_START, mrpt::math::multiply_HtCH_scalar(), and mrpt::math::wrapToPiInPlace().

Referenced by mrpt::slam::CGridMapAligner::AlignPDF_robustMatch().

Here is the call graph for this function:
Here is the caller graph for this function:

◆ operator+=() [1/2]

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

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

Definition at line 325 of file CPosePDFGaussian.cpp.

References mean, and rotateCov().

Here is the call graph for this function:

◆ operator+=() [2/2]

void 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 ).

Definition at line 525 of file CPosePDFGaussian.cpp.

References cov, mrpt::poses::CPosePDF::jacobiansPoseComposition(), mean, mrpt::math::multiply_HCHt(), and mrpt::math::UNINITIALIZED_MATRIX.

Here is the call graph for this function:

◆ 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 179 of file CPosePDFGaussian.h.

References inverseComposition().

Here is the call graph for this function:

◆ rotateCov()

void 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] $.

Definition at line 198 of file CPosePDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::asEigen(), and cov.

Referenced by changeCoordinatesReference(), mrpt::slam::CRangeBearingKFSLAM2D::OnTransitionNoise(), and operator+=().

Here is the call graph for this function:
Here is the caller graph for this function:

◆ saveToTextFile()

bool CPosePDFGaussian::saveToTextFile ( const std::string file) const
overridevirtual

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::math::CProbabilityDensityFunction< CPose2D, 3 >.

Definition at line 153 of file CPosePDFGaussian.cpp.

References cov, mrpt::system::os::fclose(), mrpt::system::os::fopen(), mrpt::system::os::fprintf(), mean, mrpt::poses::CPose2D::phi(), mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::x(), and mrpt::poses::CPoseOrPoint< DERIVEDCLASS, DIM >::y().

Here is the call graph for this function:

◆ serializeFrom() [1/2]

void CPosePDFGaussian::serializeFrom ( mrpt::serialization::CArchive in,
uint8_t  serial_version 
)
overrideprotectedvirtual

Pure virtual method for reading (deserializing) from an abstract archive.

Users don't call this method directly. Instead, use stream >> object;.

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 I/O error

Implements mrpt::serialization::CSerializable.

Definition at line 63 of file CPosePDFGaussian.cpp.

References mrpt::math::CMatrixFixed< T, ROWS, COLS >::cast_double(), cov, mrpt::math::deserializeSymmetricMatrixFrom(), mean, and MRPT_THROW_UNKNOWN_SERIALIZATION_VERSION.

Here is the call graph for this function:

◆ serializeFrom() [2/2]

virtual void mrpt::serialization::CSerializable::serializeFrom ( CSchemeArchiveBase in)
inlineprotectedvirtualinherited

Virtual method for reading (deserializing) from an abstract schema based archive.

Definition at line 74 of file CSerializable.h.

References mrpt::serialization::CSerializable::GetRuntimeClass(), and THROW_EXCEPTION.

Here is the call graph for this function:

◆ serializeGetVersion()

uint8_t CPosePDFGaussian::serializeGetVersion ( ) const
overrideprotectedvirtual

Must return the current versioning number of the object.

Start in zero for new classes, and increments each time there is a change in the stored format.

Implements mrpt::serialization::CSerializable.

Definition at line 57 of file CPosePDFGaussian.cpp.

◆ serializeTo() [1/2]

void CPosePDFGaussian::serializeTo ( mrpt::serialization::CArchive out) const
overrideprotectedvirtual

Pure virtual method for writing (serializing) to an abstract archive.

Users don't call this method directly. Instead, use stream << object;.

Exceptions
std::exceptionOn any I/O error

Implements mrpt::serialization::CSerializable.

Definition at line 58 of file CPosePDFGaussian.cpp.

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

Here is the call graph for this function:

◆ serializeTo() [2/2]

virtual void mrpt::serialization::CSerializable::serializeTo ( CSchemeArchiveBase out) const
inlineprotectedvirtualinherited

Virtual method for writing (serializing) to an abstract schema based archive.

Definition at line 64 of file CSerializable.h.

References mrpt::serialization::CSerializable::GetRuntimeClass(), and THROW_EXCEPTION.

Here is the call graph for this function:

◆ writeToMatlab()

virtual mxArray* mrpt::serialization::CSerializable::writeToMatlab ( ) const
inlinevirtualinherited

Introduces a pure virtual method responsible for writing to a mxArray Matlab object, typically a MATLAB struct whose contents are documented in each derived class.

Returns
A new mxArray (caller is responsible of memory freeing) or nullptr is class does not support conversion to MATLAB.

Definition at line 90 of file CSerializable.h.

Member Data Documentation

◆ _init_CPosePDFGaussian

mrpt::rtti::CLASSINIT mrpt::poses::CPosePDFGaussian::_init_CPosePDFGaussian
staticprotected

Definition at line 30 of file CPosePDFGaussian.h.

◆ className

constexpr const char* mrpt::poses::CPosePDFGaussian::className = "CPosePDFGaussian"
static

Definition at line 30 of file CPosePDFGaussian.h.

◆ cov

◆ mean

◆ runtimeClassId

const mrpt::rtti::TRuntimeClassId mrpt::poses::CPosePDFGaussian::runtimeClassId
staticprotected

Definition at line 30 of file CPosePDFGaussian.h.

◆ state_length

constexpr size_t mrpt::math::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 32 of file CProbabilityDensityFunction.h.




Page generated by Doxygen 1.8.14 for MRPT 1.9.9 Git: c26d46ba6 Thu Jul 18 13:03:42 2019 +0200 at jue jul 18 13:10:17 CEST 2019