mrpt::bayes::CParticleFilter Class Reference

This class acts as a common interface to the different interfaces (see CParticleFilter::TParticleFilterAlgorithm) any bayes::CParticleFilterCapable class can implement: it is the invoker of particle filter algorithms. More...

#include <mrpt/bayes/CParticleFilter.h>

Inheritance diagram for mrpt::bayes::CParticleFilter:

List of all members.

Classes
struct	TParticleFilterOptions
	The configuration of a particle filter. More...
struct	TParticleFilterStats
	Statistics for being returned from the "execute" method. More...
Public Types
enum	TParticleFilterAlgorithm { pfStandardProposal = 0, pfAuxiliaryPFStandard, pfOptimalProposal, pfAuxiliaryPFOptimal }
	Defines different types of particle filter algorithms. More...
enum	TParticleResamplingAlgorithm { prMultinomial = 0, prResidual, prStratified, prSystematic }
	Defines the different resampling algorithms. More...
Public Member Functions
	CParticleFilter ()
	Default constructor.
virtual	~CParticleFilter ()
void	executeOn (CParticleFilterCapable &obj, const mrpt::slam::CActionCollection *action, const mrpt::slam::CSensoryFrame *observation, TParticleFilterStats *stats=NULL)
	Executes a complete prediction + update step of the selected particle filtering algorithm.
Public Attributes
CParticleFilter::TParticleFilterOptions	m_options
	The options to be used in the PF, must be set before executing any step of the particle filter.

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Detailed Description

This class acts as a common interface to the different interfaces (see CParticleFilter::TParticleFilterAlgorithm) any bayes::CParticleFilterCapable class can implement: it is the invoker of particle filter algorithms.

The particle filter is executed on a probability density function (PDF) described by a CParticleFilterCapable object, passed in the constructor or alternatively through the CParticleFilter::executeOn method.

For a complete example and further details, see the Particle Filter tutorial.

The basic SIR algorithm (pfStandardProposal) consists of:

• Execute a prediction with the given "action".
• Update the weights of the particles using the likelihood of the "observation".
• Normalize weights.
• Perform resampling if the ESS is below the threshold options.BETA.

See also:

mrpt::poses::CPoseParticlesPDF

Definition at line 63 of file CParticleFilter.h.

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Member Enumeration Documentation

enum mrpt::bayes::CParticleFilter::TParticleFilterAlgorithm

Defines different types of particle filter algorithms.

The defined SIR implementations are:

• pfStandardProposal: Standard proposal distribution + weights according to likelihood function.
• pfAuxiliaryPFStandard: An auxiliary PF using the standard proposal distribution.
• pfOptimalProposal: Use the optimal proposal distribution (where available!, usually this will perform approximations)
• pfAuxiliaryPFOptimal: Use the optimal proposal and a auxiliary particle filter (see paper).

See the theoretical discussion in resampling schemes.

Enumerator:

pfStandardProposal
pfAuxiliaryPFStandard
pfOptimalProposal
pfAuxiliaryPFOptimal

Definition at line 76 of file CParticleFilter.h.

enum mrpt::bayes::CParticleFilter::TParticleResamplingAlgorithm

Defines the different resampling algorithms.

The implemented resampling methods are:

• prMultinomial (Default): Uses standard select with replacement (draws M random uniform numbers)
• prResidual: The residual or "remainder" method.
• prStratified: The stratified resampling, where a uniform sample is drawn for each of M subdivisions of the range (0,1].
• prSystematic: A single uniform sample is drawn in the range (0,1/M].

See the theoretical discussion in resampling schemes.

Enumerator:

prMultinomial
prResidual
prStratified
prSystematic

Definition at line 93 of file CParticleFilter.h.

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Constructor & Destructor Documentation

mrpt::bayes::CParticleFilter::CParticleFilter

(

)

Default constructor.

After creating the PF object, set the options in CParticleFilter::m_options, then execute steps through CParticleFilter::executeOn.

virtual mrpt::bayes::CParticleFilter::~CParticleFilter

(

)

[inline, virtual]

Definition at line 171 of file CParticleFilter.h.

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Member Function Documentation

void mrpt::bayes::CParticleFilter::executeOn	(	CParticleFilterCapable &	obj,
		const mrpt::slam::CActionCollection *	action,
		const mrpt::slam::CSensoryFrame *	observation,
		TParticleFilterStats *	stats = NULL
	)

Executes a complete prediction + update step of the selected particle filtering algorithm.

The member CParticleFilter::m_options must be set before calling this to settle the algorithm parameters.

Parameters:

	obj	The object representing the probability distribution function (PDF) which apply the particle filter algorithm to.
	action	A pointer to an action in the form of a CActionCollection, or NULL if there is no action.
	observation	A pointer to observations in the form of a CSensoryFrame, or NULL if there is no observation.
	stats	An output structure for gathering statistics of the particle filter execution, or set to NULL if you do not need it (see CParticleFilter::TParticleFilterStats).

See also:

CParticleFilterCapable, executeOn

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Member Data Documentation

CParticleFilter::TParticleFilterOptions mrpt::bayes::CParticleFilter::m_options

The options to be used in the PF, must be set before executing any step of the particle filter.

Definition at line 192 of file CParticleFilter.h.