class mrpt::hmtslam::CLSLAM_RBPF_2DLASER

Implements a 2D local SLAM method based on a RBPF over an occupancy grid map.

This class is used internally in mrpt::slam::CHMTSLAM

#include <mrpt/hmtslam/CHMTSLAM.h>

class CLSLAM_RBPF_2DLASER: public mrpt::hmtslam::CLSLAMAlgorithmBase
{
public:
    // structs

    struct TPathBin;

    // construction

    CLSLAM_RBPF_2DLASER(CHMTSLAM* parent);

    //
methods

    virtual void processOneLMH(CLocalMetricHypothesis* LMH, const mrpt::obs::CActionCollection::Ptr& act, const mrpt::obs::CSensoryFrame::Ptr& sf);
    virtual void prediction_and_update_pfAuxiliaryPFOptimal(CLocalMetricHypothesis* LMH, const mrpt::obs::CActionCollection* action, const mrpt::obs::CSensoryFrame* observation, const bayes::CParticleFilter::TParticleFilterOptions& PF_options);
    virtual void prediction_and_update_pfOptimalProposal(CLocalMetricHypothesis* LMH, const mrpt::obs::CActionCollection* action, const mrpt::obs::CSensoryFrame* observation, const bayes::CParticleFilter::TParticleFilterOptions& PF_options);
};

Inherited Members

public:
    //
methods

    virtual void processOneLMH(CLocalMetricHypothesis* LMH, const mrpt::obs::CActionCollection::Ptr& act, const mrpt::obs::CSensoryFrame::Ptr& sf) = 0;
    virtual void prediction_and_update_pfAuxiliaryPFOptimal(CLocalMetricHypothesis* LMH, const mrpt::obs::CActionCollection* action, const mrpt::obs::CSensoryFrame* observation, const bayes::CParticleFilter::TParticleFilterOptions& PF_options) = 0;
    virtual void prediction_and_update_pfOptimalProposal(CLocalMetricHypothesis* LMH, const mrpt::obs::CActionCollection* action, const mrpt::obs::CSensoryFrame* observation, const bayes::CParticleFilter::TParticleFilterOptions& PF_options) = 0;

Construction

CLSLAM_RBPF_2DLASER(CHMTSLAM* parent)

Constructor.

Methods

virtual void processOneLMH(CLocalMetricHypothesis* LMH, const mrpt::obs::CActionCollection::Ptr& act, const mrpt::obs::CSensoryFrame::Ptr& sf)

Main entry point from HMT-SLAM: process some actions & observations.

The passed action/observation will be deleted, so a copy must be made if necessary. This method must be in charge of updating the robot pose estimates and also to update the map when required.

Parameters:

LMH	The local metric hypothesis which must be updated by this SLAM algorithm.
act	The action to process (or nullptr).
sf	The observations to process (or nullptr).

virtual void prediction_and_update_pfAuxiliaryPFOptimal(
    CLocalMetricHypothesis* LMH,
    const mrpt::obs::CActionCollection* action,
    const mrpt::obs::CSensoryFrame* observation,
    const bayes::CParticleFilter::TParticleFilterOptions& PF_options
    )

The PF algorithm implementation.

The PF algorithm implementation for “optimal sampling for non-parametric observation models”.

virtual void prediction_and_update_pfOptimalProposal(
    CLocalMetricHypothesis* LMH,
    const mrpt::obs::CActionCollection* action,
    const mrpt::obs::CSensoryFrame* observation,
    const bayes::CParticleFilter::TParticleFilterOptions& PF_options
    )

The PF algorithm implementation.

The PF algorithm implementation for “optimal sampling” approximated with scan matching (Stachniss method)