data_association.h File Reference

#include <mrpt/math/CMatrixDynamic.h>
#include <mrpt/poses/CPoint2DPDFGaussian.h>
#include <mrpt/poses/CPointPDFGaussian.h>
#include <mrpt/typemeta/TEnumType.h>

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Classes
struct	mrpt::slam::TDataAssociationResults
	The results from mrpt::slam::data_association. More...

Namespaces
	mrpt::slam

Functions
	MRPT_FILL_ENUM (assocNN)
	MRPT_FILL_ENUM (assocJCBB)
	MRPT_FILL_ENUM (metricMaha)
	MRPT_FILL_ENUM (metricML)

Data association
enum	mrpt::slam::TDataAssociationMethod { mrpt::slam::assocNN = 0, mrpt::slam::assocJCBB }
	Different algorithms for data association, used in mrpt::slam::data_association. More...
enum	mrpt::slam::TDataAssociationMetric { mrpt::slam::metricMaha = 0, mrpt::slam::metricML }
	Different metrics for data association, used in mrpt::slam::data_association For a comparison of both methods see paper: More...
using	mrpt::slam::observation_index_t = size_t
	Used in mrpt::slam::TDataAssociationResults. More...
using	mrpt::slam::prediction_index_t = size_t
	Used in mrpt::slam::TDataAssociationResults. More...
void	mrpt::slam::data_association_full_covariance (const mrpt::math::CMatrixDouble &Z_observations_mean, const mrpt::math::CMatrixDouble &Y_predictions_mean, const mrpt::math::CMatrixDouble &Y_predictions_cov, TDataAssociationResults &results, const TDataAssociationMethod method=assocJCBB, const TDataAssociationMetric metric=metricMaha, const double chi2quantile=0.99, const bool DAT_ASOC_USE_KDTREE=true, const std::vector< prediction_index_t > &predictions_IDs=std::vector< prediction_index_t >(), const TDataAssociationMetric compatibilityTestMetric=metricMaha, const double log_ML_compat_test_threshold=0.0)
	Computes the data-association between the prediction of a set of landmarks and their observations, all of them with covariance matrices - Generic version with prediction full cross-covariances. More...
void	mrpt::slam::data_association_independent_predictions (const mrpt::math::CMatrixDouble &Z_observations_mean, const mrpt::math::CMatrixDouble &Y_predictions_mean, const mrpt::math::CMatrixDouble &Y_predictions_cov, TDataAssociationResults &results, const TDataAssociationMethod method=assocJCBB, const TDataAssociationMetric metric=metricMaha, const double chi2quantile=0.99, const bool DAT_ASOC_USE_KDTREE=true, const std::vector< prediction_index_t > &predictions_IDs=std::vector< prediction_index_t >(), const TDataAssociationMetric compatibilityTestMetric=metricMaha, const double log_ML_compat_test_threshold=0.0)
	Computes the data-association between the prediction of a set of landmarks and their observations, all of them with covariance matrices - Generic version with NO prediction cross-covariances. More...

Function Documentation

MRPT_FILL_ENUM() [1/4]

MRPT_FILL_ENUM

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assocNN

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MRPT_FILL_ENUM() [2/4]

MRPT_FILL_ENUM

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assocJCBB

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MRPT_FILL_ENUM() [3/4]

MRPT_FILL_ENUM

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metricMaha

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MRPT_FILL_ENUM() [4/4]

MRPT_FILL_ENUM

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metricML

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