MRPT  1.9.9
Classes | Namespaces | Functions
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>
Include dependency graph for data_association.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 ( assocNN  )

◆ MRPT_FILL_ENUM() [2/4]

MRPT_FILL_ENUM ( assocJCBB  )

◆ MRPT_FILL_ENUM() [3/4]

MRPT_FILL_ENUM ( metricMaha  )

◆ MRPT_FILL_ENUM() [4/4]

MRPT_FILL_ENUM ( metricML  )



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