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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 mrpt::utils::CProbabilityDensityFunction< CPose3D, 6 >

List of all members.

Classes

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

Public Types

typedef std::deque< TGaussianMode > TModesList
typedef std::deque
< TGaussianMode >
::const_iterator 		const_iterator
typedef std::deque
< TGaussianMode >::iterator 		iterator

Public Member Functions

 CPose3DPDFSOG (size_t nModes=1)
 Default constructor.
void clear ()
 Clear all the gaussian modes.
void resize (const size_t N)
 Set the number of SOG modes.
size_t size () const
 Return the number of Gaussian modes.
bool empty () const
 Return whether there is any Gaussian mode.
iterator begin ()
iterator end ()
const_iterator begin () const
const_iterator end () const
void getMean (CPose3D &mean_pose) const
 Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF), computed as a weighted average over all m_particles.
void getCovarianceAndMean (CMatrixDouble66 &cov, CPose3D &mean_point) const
 Returns an estimate of the pose covariance matrix (6x6 cov matrix) and the mean, both at once.
void normalizeWeights ()
 Normalize the weights in m_modes such as the maximum log-weight is 0.
void getMostLikelyMode (CPose3DPDFGaussian &outVal) const
 Return the Gaussian mode with the highest likelihood (or an empty Gaussian if there are no modes in this SOG).
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.

Protected Member Functions

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

Protected Attributes

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

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.

Member Typedef Documentation

typedef std::deque<TGaussianMode>::const_iterator mrpt::poses::CPose3DPDFSOG::const_iterator

Definition at line 76 of file CPose3DPDFSOG.h.

typedef std::deque<TGaussianMode>::iterator mrpt::poses::CPose3DPDFSOG::iterator

Definition at line 77 of file CPose3DPDFSOG.h.

typedef std::deque<TGaussianMode> mrpt::poses::CPose3DPDFSOG::TModesList

Definition at line 75 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.

const_iterator mrpt::poses::CPose3DPDFSOG::begin (  )  const [inline]

Definition at line 103 of file CPose3DPDFSOG.h.

iterator mrpt::poses::CPose3DPDFSOG::begin (  )  [inline]

Definition at line 101 of file CPose3DPDFSOG.h.

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::utils::CProbabilityDensityFunction< CPose3D, 6 >.

void mrpt::poses::CPose3DPDFSOG::clear (  ) 

Clear all the gaussian modes.

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.

Reimplemented from mrpt::utils::CProbabilityDensityFunction< CPose3D, 6 >.

void mrpt::poses::CPose3DPDFSOG::drawSingleSample ( CPose3D &  outPart  )  const

Draws a single sample from the distribution.

bool mrpt::poses::CPose3DPDFSOG::empty (  )  const [inline]

Return whether there is any Gaussian mode.

Definition at line 99 of file CPose3DPDFSOG.h.

const_iterator mrpt::poses::CPose3DPDFSOG::end (  )  const [inline]

Definition at line 104 of file CPose3DPDFSOG.h.

iterator mrpt::poses::CPose3DPDFSOG::end (  )  [inline]

Definition at line 102 of file CPose3DPDFSOG.h.

void mrpt::poses::CPose3DPDFSOG::getCovarianceAndMean ( CMatrixDouble66 &  cov,
CPose3D &  mean_point 
) const

Returns an estimate of the pose covariance matrix (6x6 cov matrix) and the mean, both at once.

See also:
getMean

void mrpt::poses::CPose3DPDFSOG::getMean ( CPose3D &  mean_pose  )  const

Returns an estimate of the pose, (the mean, or mathematical expectation of the PDF), computed as a weighted average over all m_particles.

See also:
getCovariance

void mrpt::poses::CPose3DPDFSOG::getMostLikelyMode ( CPose3DPDFGaussian &  outVal  )  const

Return the Gaussian mode with the highest likelihood (or an empty Gaussian if there are no modes in this SOG).

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::resize ( const size_t  N  ) 

Set the number of SOG modes.

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::utils::CProbabilityDensityFunction< CPose3D, 6 >.

size_t mrpt::poses::CPose3DPDFSOG::size (  )  const [inline]

Return the number of Gaussian modes.

Definition at line 98 of file CPose3DPDFSOG.h.

Member Data Documentation

TModesList mrpt::poses::CPose3DPDFSOG::m_modes [protected]

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

Note that no weight can be zero!! We must use pointers to satisfy the mem-alignment of the matrixes

Definition at line 88 of file CPose3DPDFSOG.h.



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