#include <mrpt/utils/utils_defs.h>
#include <mrpt/poses/CPoint2DPDFGaussian.h>
#include <mrpt/poses/CPointPDFGaussian.h>
#include <mrpt/slam/link_pragmas.h>
Go to the source code of this file.
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 Programming 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 SLAM_IMPEXP | 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. | |
void SLAM_IMPEXP | 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. |
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