Public Member Functions | List of all members
BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit Class Referenceabstract

Class for linear analytic measurementmodels with additive gaussian noise. More...

#include <linearanalyticmeasurementmodel_gaussianuncertainty_implicit.h>

Inheritance diagram for BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit:
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Public Member Functions

virtual void Calculate (const MatrixWrapper::ColumnVector &x, const MatrixWrapper::ColumnVector &z, const MatrixWrapper::Matrix &R)=0
 
virtual MatrixWrapper::SymmetricMatrix & CovarianceGet ()=0
 Returns covariance of the noise on the linearised measurement model evaluated using measurements z and states x. More...
 
virtual MatrixWrapper::SymmetricMatrix CovarianceGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)=0
 Returns covariance of the noise on the linearised measurement model evaluated using current z and states x. More...
 
virtual MatrixWrapper::Matrix df_dxGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)=0
 Returns H-matrix calculated with measurement z and state x. More...
 
virtual MatrixWrapper::Matrix & df_dzGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)=0
 Returns D-matrix calculated with measurement z and state x. More...
 
virtual MatrixWrapper::Matrix & dfGet (int number)=0
 
virtual MatrixWrapper::ColumnVector ExpectedValueGet ()=0
 Return a prediction for the mean of the noise on the linear measurement equation, using the current x and z. More...
 
virtual const MatrixWrapper::ColumnVector & fGet () const =0
 
virtual const int & Is_Identity () const =0
 Returns 1 if D-matrix equals the identity matrix else 0. More...
 
 LinearAnalyticMeasurementModelGaussianUncertainty_Implicit (LinearAnalyticConditionalGaussian *pdf)
 Constructor. More...
 
 LinearAnalyticMeasurementModelGaussianUncertainty_Implicit ()
 Constructor. More...
 
virtual MatrixWrapper::ColumnVector PredictionGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)=0
 Return a prediction for the mean of the noise on the linear measurement equation, calculated with measurements z and state x. More...
 
virtual const MatrixWrapper::Matrix & SRCovariance () const =0
 Returns square root of the covariance of the measurements z. More...
 
virtual const int TypeGet () const =0
 
virtual ~LinearAnalyticMeasurementModelGaussianUncertainty_Implicit ()
 Destructor. More...
 
- Public Member Functions inherited from BFL::LinearAnalyticMeasurementModelGaussianUncertainty
const MatrixWrapper::Matrix & HGet () const
 Get Matrix H. More...
 
void HSet (const MatrixWrapper::Matrix &h)
 Set Matrix H. More...
 
const MatrixWrapper::Matrix & JGet () const
 Get Matrix J. More...
 
void JSet (const MatrixWrapper::Matrix &j)
 Set Matrix J. More...
 
 LinearAnalyticMeasurementModelGaussianUncertainty (LinearAnalyticConditionalGaussian *pdf=NULL)
 Constructor. More...
 
virtual ~LinearAnalyticMeasurementModelGaussianUncertainty ()
 
- Public Member Functions inherited from BFL::AnalyticMeasurementModelGaussianUncertainty
 AnalyticMeasurementModelGaussianUncertainty (AnalyticConditionalGaussian *Measurementpdf=NULL)
 Constructor. More...
 
virtual ~AnalyticMeasurementModelGaussianUncertainty ()
 Destructor. More...
 
- Public Member Functions inherited from BFL::MeasurementModel< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector >
 MeasurementModel (ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > *Measurementpdf=NULL)
 Constructor. More...
 
ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > * MeasurementPdfGet ()
 Get the MeasurementPDF. More...
 
void MeasurementPdfSet (ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > *pdf)
 Set the MeasurementPDF. More...
 
int MeasurementSizeGet () const
 Get Measurement Size. More...
 
Probability ProbabilityGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x, const MatrixWrapper::ColumnVector &s)
 Get the probability of a certain measurement. More...
 
Probability ProbabilityGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)
 Get the probability of a certain measurement. More...
 
MatrixWrapper::ColumnVector Simulate (const MatrixWrapper::ColumnVector &x, const MatrixWrapper::ColumnVector &s, int sampling_method=DEFAULT, void *sampling_args=NULL)
 Simulate the Measurement, given a certain state, and an input. More...
 
MatrixWrapper::ColumnVector Simulate (const MatrixWrapper::ColumnVector &x, int sampling_method=DEFAULT, void *sampling_args=NULL)
 Simulate the system (no input system) More...
 
bool SystemWithoutSensorParams () const
 Number of Conditional Arguments. More...
 
virtual ~MeasurementModel ()
 Destructor. More...
 

Additional Inherited Members

- Protected Attributes inherited from BFL::MeasurementModel< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector >
ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > * _MeasurementPdf
 ConditionalPdf representing $ P(Z_k | X_{k}, U_{k}) $. More...
 
bool _systemWithoutSensorParams
 System with no sensor params?? More...
 

Detailed Description

Class for linear analytic measurementmodels with additive gaussian noise.

This class represents all measurement models of the form

\[ 0 = f (x,z) \]

as a linear measurement model with virtual measurement z_k^{virtual}

\[ z_k^{virtual} = H(x_k,z_k) \times x_k + N(\mu(x_{k},z_k) ,\Sigma(x_k,z_k)) \]

Definition at line 37 of file linearanalyticmeasurementmodel_gaussianuncertainty_implicit.h.

Constructor & Destructor Documentation

◆ LinearAnalyticMeasurementModelGaussianUncertainty_Implicit() [1/2]

BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit ( LinearAnalyticConditionalGaussian pdf)

Constructor.

Parameters
pdfConditional pdf, with Gaussian uncertainty

Definition at line 27 of file linearanalyticmeasurementmodel_gaussianuncertainty_implicit.cpp.

◆ LinearAnalyticMeasurementModelGaussianUncertainty_Implicit() [2/2]

BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit ( )

Constructor.

Definition at line 32 of file linearanalyticmeasurementmodel_gaussianuncertainty_implicit.cpp.

◆ ~LinearAnalyticMeasurementModelGaussianUncertainty_Implicit()

BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::~LinearAnalyticMeasurementModelGaussianUncertainty_Implicit ( )
virtual

Member Function Documentation

◆ Calculate()

virtual void BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::Calculate ( const MatrixWrapper::ColumnVector &  x,
const MatrixWrapper::ColumnVector &  z,
const MatrixWrapper::Matrix &  R 
)
pure virtual

◆ CovarianceGet() [1/2]

virtual MatrixWrapper::SymmetricMatrix& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::CovarianceGet ( )
pure virtual

Returns covariance of the noise on the linearised measurement model evaluated using measurements z and states x.

The linearised measurement equation look like:

\[ z_k^{virtual} = H(x_{k},z_k) \times x_k + N(\mu(x_{k},z_k) ,\Sigma(x_k,z_k)) \]

with noise

\[ =N(\mu(x_{k},z_k), \Sigma(x_k,z_k))\]

and covariance

\[ \Sigma(x_k,z_k)= D(x_k,z_k)*R*D(x_k,z_k)' \]

and R the noise on the measurements z .

◆ CovarianceGet() [2/2]

virtual MatrixWrapper::SymmetricMatrix BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::CovarianceGet ( const MatrixWrapper::ColumnVector &  z,
const MatrixWrapper::ColumnVector &  x 
)
pure virtual

Returns covariance of the noise on the linearised measurement model evaluated using current z and states x.

The linearised measurement equation look like:

\[ z_k^{virtual} = H(x_{k},z_k) \times x_k + N(\mu(x_{k},z_k) ,\Sigma(x_k,z_k)) \]

with noise

\[ =N(\mu(x_{k},z_k), \Sigma(x_k,z_k))\]

and covariance

\[ \Sigma(x_k,z_k)= D(x_k,z_k)*R*D(x_k,z_k)' \]

and R the noise on the measurements z .

Reimplemented from BFL::LinearAnalyticMeasurementModelGaussianUncertainty.

◆ df_dxGet()

virtual MatrixWrapper::Matrix BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::df_dxGet ( const MatrixWrapper::ColumnVector &  z,
const MatrixWrapper::ColumnVector &  x 
)
pure virtual

Returns H-matrix calculated with measurement z and state x.

\[ H = \frac{df}{dx} \mid_{ z, x} \]

used to determine the covariance of noise on the linear measurement equation

Parameters
zThe value of the input in which the derivate is evaluated
xThe value in the state in which the derivate is evaluated

Reimplemented from BFL::LinearAnalyticMeasurementModelGaussianUncertainty.

◆ df_dzGet()

virtual MatrixWrapper::Matrix& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::df_dzGet ( const MatrixWrapper::ColumnVector &  z,
const MatrixWrapper::ColumnVector &  x 
)
pure virtual

Returns D-matrix calculated with measurement z and state x.

\[ D = \frac{df}{dz} \mid_{ z, x} \]

used to determine the covariance of noise on the linear measurement equation

Parameters
zThe value of the input in which the derivate is evaluated
xThe value in the state in which the derivate is evaluated

◆ dfGet()

virtual MatrixWrapper::Matrix& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::dfGet ( int  number)
pure virtual

◆ ExpectedValueGet()

virtual MatrixWrapper::ColumnVector BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::ExpectedValueGet ( )
pure virtual

Return a prediction for the mean of the noise on the linear measurement equation, using the current x and z.

◆ fGet()

virtual const MatrixWrapper::ColumnVector& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::fGet ( ) const
pure virtual

◆ Is_Identity()

virtual const int& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::Is_Identity ( ) const
pure virtual

Returns 1 if D-matrix equals the identity matrix else 0.

◆ PredictionGet()

virtual MatrixWrapper::ColumnVector BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::PredictionGet ( const MatrixWrapper::ColumnVector &  z,
const MatrixWrapper::ColumnVector &  x 
)
pure virtual

Return a prediction for the mean of the noise on the linear measurement equation, calculated with measurements z and state x.

Reimplemented from BFL::LinearAnalyticMeasurementModelGaussianUncertainty.

◆ SRCovariance()

virtual const MatrixWrapper::Matrix& BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::SRCovariance ( ) const
pure virtual

Returns square root of the covariance of the measurements z.

◆ TypeGet()

virtual const int BFL::LinearAnalyticMeasurementModelGaussianUncertainty_Implicit::TypeGet ( ) const
pure virtual

The documentation for this class was generated from the following files:


bfl
Author(s): Klaas Gadeyne, Wim Meeussen, Tinne Delaet and many others. See web page for a full contributor list. ROS package maintained by Wim Meeussen.
autogenerated on Mon Feb 28 2022 21:56:34