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mrpt::poses::CPose3DPDFSOG Class Reference

Declares a class that represents a Probability Density function (PDF) of a 3D(6D) pose $ p(\mathbf{x}) = [x ~ y ~ z ~ yaw ~ pitch ~ roll]^t $. More...

#include <mrpt/poses/CPose3DPDFSOG.h>

Inheritance diagram for mrpt::poses::CPose3DPDFSOG:

mrpt::poses::CPose3DPDF mrpt::utils::CSerializable

List of all members.

Classes

struct  TGaussianMode
 The struct for each mode:. More...

Public Member Functions

 CPose3DPDFSOG (size_t nModes=1)
 Default constructor.
CPose3D getEstimatedPose () const
 Returns an estimate of the point, (the mean, or mathematical expectation of the PDF).
CMatrixD getEstimatedCovariance () const
 Returns an estimate of the pose covariance matrix (a 6x6 matrix for the variables x,y,z,yaw,pitch,roll).
void normalizeWeights ()
 Normalize the weights in m_modes such as the maximum log-weight is 0.
void copyFrom (const CPose3DPDF &o)
 Copy operator, translating if necesary (for example, between particles and gaussian representations).
void saveToTextFile (const std::string &file) const
 Save the density to a text file, with the following format: There is one row per Gaussian "mode", and each row contains 10 elements:
  • w (The linear weight)
  • x_mean (gaussian mean value)
  • y_mean (gaussian mean value)
  • x_mean (gaussian mean value)
  • yaw_mean (gaussian mean value, in radians)
  • pitch_mean (gaussian mean value, in radians)
  • roll_mean (gaussian mean value, in radians)
  • C11,C22,C33,C44,C55,C66 (Covariance elements)
  • C12,C13,C14,C15,C16 (Covariance elements)
  • C23,C24,C25,C25 (Covariance elements)
  • C34,C35,C36 (Covariance elements)
  • C45,C46 (Covariance elements)
  • C56 (Covariance elements).

void changeCoordinatesReference (const CPose3D &newReferenceBase)
 This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which "to project" the current pdf.
void bayesianFusion (CPose3DPDF &p1, CPose3DPDF &p2)
 Bayesian fusion of two pose distributions, then save the result in this object (WARNING: Currently p1 must be a mrpt::poses::CPose3DPDFSOG object and p2 a mrpt::poses::CPose3DPDFSOG object).
void drawSingleSample (CPose3D &outPart) const
 Draws a single sample from the distribution.
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 1x6 vectors, where each row contains a (x,y,z,yaw,pitch,roll) datum.
void inverse (CPose3DPDF &o) const
 Returns a new PDF such as: NEW_PDF = (0,0,0) - THIS_PDF.
void appendFrom (const CPose3DPDFSOG &o)
 Append the Gaussian modes from "o" to the current set of modes of "this" density.

Public Attributes

std::deque< TGaussianModem_modes
 Access directly to this array for modify the modes as desired.

Protected Member Functions

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


Detailed Description

Declares a class that represents a Probability Density function (PDF) of a 3D(6D) pose $ p(\mathbf{x}) = [x ~ y ~ z ~ yaw ~ pitch ~ roll]^t $.

This class implements that PDF as the following multi-modal Gaussian distribution:

$ p(\mathbf{x}) = \sum\limits_{i=1}^N \omega^i \mathcal{N}( \mathbf{x} ; \bar{\mathbf{x}}^i, \mathbf{\Sigma}^i ) $

Where the number of modes N is the size of CPose3DPDFSOG::m_modes. Angles are always in radians.

See mrpt::poses::CPose3DPDF for more details.

See also:
CPose3DPDF

Definition at line 53 of file CPose3DPDFSOG.h.


Constructor & Destructor Documentation

mrpt::poses::CPose3DPDFSOG::CPose3DPDFSOG ( size_t  nModes = 1  ) 

Default constructor.

Parameters:
nModes The initial size of CPose3DPDFSOG::m_modes


Member Function Documentation

void mrpt::poses::CPose3DPDFSOG::appendFrom ( const CPose3DPDFSOG o  ) 

Append the Gaussian modes from "o" to the current set of modes of "this" density.

void mrpt::poses::CPose3DPDFSOG::assureSymmetry (  )  [protected]

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

void mrpt::poses::CPose3DPDFSOG::bayesianFusion ( CPose3DPDF p1,
CPose3DPDF p2 
) [virtual]

Bayesian fusion of two pose distributions, then save the result in this object (WARNING: Currently p1 must be a mrpt::poses::CPose3DPDFSOG object and p2 a mrpt::poses::CPose3DPDFSOG object).

Implements mrpt::poses::CPose3DPDF.

void mrpt::poses::CPose3DPDFSOG::changeCoordinatesReference ( const CPose3D newReferenceBase  )  [virtual]

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::CPose3DPDF.

void mrpt::poses::CPose3DPDFSOG::copyFrom ( const CPose3DPDF o  )  [virtual]

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

Implements mrpt::poses::CPose3DPDF.

void mrpt::poses::CPose3DPDFSOG::drawManySamples ( size_t  N,
std::vector< vector_double > &  outSamples 
) const [virtual]

Draws a number of samples from the distribution, and saves as a list of 1x6 vectors, where each row contains a (x,y,z,yaw,pitch,roll) datum.

Implements mrpt::poses::CPose3DPDF.

void mrpt::poses::CPose3DPDFSOG::drawSingleSample ( CPose3D outPart  )  const [virtual]

Draws a single sample from the distribution.

Implements mrpt::poses::CPose3DPDF.

CMatrixD mrpt::poses::CPose3DPDFSOG::getEstimatedCovariance (  )  const [virtual]

Returns an estimate of the pose covariance matrix (a 6x6 matrix for the variables x,y,z,yaw,pitch,roll).

Implements mrpt::poses::CPose3DPDF.

CPose3D mrpt::poses::CPose3DPDFSOG::getEstimatedPose (  )  const [virtual]

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

Implements mrpt::poses::CPose3DPDF.

void mrpt::poses::CPose3DPDFSOG::inverse ( CPose3DPDF o  )  const [virtual]

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

Implements mrpt::poses::CPose3DPDF.

void mrpt::poses::CPose3DPDFSOG::normalizeWeights (  ) 

Normalize the weights in m_modes such as the maximum log-weight is 0.

void mrpt::poses::CPose3DPDFSOG::saveToTextFile ( const std::string &  file  )  const [virtual]

Save the density to a text file, with the following format: There is one row per Gaussian "mode", and each row contains 10 elements:

  • w (The linear weight)
  • x_mean (gaussian mean value)
  • y_mean (gaussian mean value)
  • x_mean (gaussian mean value)
  • yaw_mean (gaussian mean value, in radians)
  • pitch_mean (gaussian mean value, in radians)
  • roll_mean (gaussian mean value, in radians)
  • C11,C22,C33,C44,C55,C66 (Covariance elements)
  • C12,C13,C14,C15,C16 (Covariance elements)
  • C23,C24,C25,C25 (Covariance elements)
  • C34,C35,C36 (Covariance elements)
  • C45,C46 (Covariance elements)
  • C56 (Covariance elements).

Implements mrpt::poses::CPose3DPDF.


Member Data Documentation

Access directly to this array for modify the modes as desired.

Note that no weight can be zero!!

Definition at line 88 of file CPose3DPDFSOG.h.




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