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| enum | mrpt::slam::TDataAssociationMethod { mrpt::slam::assocNN = 0,
mrpt::slam::assocJCBB
} |
| | Different algorithms for data association, used in mrpt::slam::data_association. More...
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| 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...
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| using | mrpt::slam::observation_index_t = size_t |
| | Used in mrpt::slam::TDataAssociationResults. More...
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| using | mrpt::slam::prediction_index_t = size_t |
| | Used in mrpt::slam::TDataAssociationResults. More...
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| 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...
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| 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...
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