data_association.h File Reference

#include <mrpt/utils/utils_defs.h>
#include <mrpt/poses/CPoint2DPDFGaussian.h>
#include <mrpt/poses/CPointPDFGaussian.h>

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Classes
struct	mrpt::slam::TDataAssociationResults
	The results from mrpt::slam::data_association. More...
Namespaces
namespace	mrpt
	This is the global namespace for all Mobile Robot Porgramming Toolkit (MRPT) libraries.
namespace	mrpt::slam
	This namespace contains algorithms for SLAM, localization, map building, representation of robot's actions and observations, and representation of many kinds of metric maps.
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. More...
typedef size_t	mrpt::slam::observation_index_t
	Used in mrpt::slam::TDataAssociationResults.
typedef size_t	mrpt::slam::prediction_index_t
	Used in mrpt::slam::TDataAssociationResults.
void MRPTDLLIMPEXP	mrpt::slam::data_association_full_covariance (const mrpt::math::CMatrixDouble &Z_observations_mean, const mrpt::math::CMatrixDouble &Z_observations_covs, 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 >())
	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.
void MRPTDLLIMPEXP	mrpt::slam::data_association_independent_predictions (const mrpt::math::CMatrixDouble &Z_observations_mean, const mrpt::math::CMatrixDouble &Z_observations_covs, 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 >())
	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.
void MRPTDLLIMPEXP	mrpt::slam::data_association_independent_2d_points (const std::vector< mrpt::poses::CPoint2DPDFGaussian > observations, const std::vector< mrpt::poses::CPoint2DPDFGaussian > predictions, 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 >())
	Computes the data-association between the prediction of a set of landmarks and their observations, all of them with covariance matrices - Specialized version for 2D points with NO prediction cross-covariances.
void MRPTDLLIMPEXP	mrpt::slam::data_association_independent_3d_points (const std::vector< mrpt::poses::CPointPDFGaussian > observations, const std::vector< mrpt::poses::CPointPDFGaussian > predictions, 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 >())
	Computes the data-association between the prediction of a set of landmarks and their observations, all of them with covariance matrices - Specialized version for 3D points with NO prediction cross-covariances.