Maximum Likelihood Method class, used to match observations to landmarks in the map with maximum likelihood method It uses the Mahalanobis distance to determine the best match It also uses a gate to determine if the match is valid The Mahalanobis distance is calculated as the square root of the innovation covariance The gate is a threshold that the Mahalanobis distance must be below to be considered a valid match The gate is defined as the normalized innovation squared (NIS) gate Normalized Distance. More...

#include <data_association.hpp>

Inheritance diagram for MaxLikelihood:

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Public Member Functions
int	associate_n_filter (const std::vector< common_lib::structures::Cone > &perception_map, Eigen::VectorXf &_x_vector_, Eigen::MatrixXf &_p_matrix_, std::vector< int > &matched_ids, std::vector< Eigen::Vector2f > &matched_cone_positions, std::vector< Eigen::Vector2f > &new_features, ObservationModel *observation_model) const override
	normalized distance gate (closest unmatched landmark)

	MaxLikelihood (float max_landmark_distance)
	Construct a new Max Likelihood object.

Public Member Functions inherited from DataAssociationModel
	DataAssociationModel (float max_landmark_distance)

virtual	~DataAssociationModel ()=default

	DataAssociationModel ()=default

	DataAssociationModel (DataAssociationParameters params)

virtual	~DataAssociationModel ()=default

virtual Eigen::VectorXi	associate (const Eigen::VectorXd &landmarks, const Eigen::VectorXd &observations, const Eigen::MatrixXd &covariance, const Eigen::VectorXd &observation_confidences) const =0
	This function associates the landmarks with the observations.

Static Public Attributes
static float	association_gate_ = 4.991f

static float	new_landmark_gate_ = 20.0f
	normalized innovation squared gate

Additional Inherited Members
Protected Member Functions inherited from DataAssociationModel
float	get_max_landmark_distance () const

Protected Attributes inherited from DataAssociationModel
DataAssociationParameters	_params_

Detailed Description

Maximum Likelihood Method class, used to match observations to landmarks in the map with maximum likelihood method It uses the Mahalanobis distance to determine the best match It also uses a gate to determine if the match is valid The Mahalanobis distance is calculated as the square root of the innovation covariance The gate is a threshold that the Mahalanobis distance must be below to be considered a valid match The gate is defined as the normalized innovation squared (NIS) gate Normalized Distance.

Definition at line 71 of file data_association.hpp.

Constructor & Destructor Documentation

◆ MaxLikelihood()

MaxLikelihood::MaxLikelihood ( float max_landmark_distance )

explicit

Construct a new Max Likelihood object.

Parameters

max_landmark_distance Maximum distance from the car to an observed landmark for it to be considered in the state estimation

Definition at line 20 of file data_association.cpp.

Member Function Documentation

◆ associate_n_filter()

int MaxLikelihood::associate_n_filter	(	const std::vector< common_lib::structures::Cone > &	perception_map,
		Eigen::VectorXf &	_x_vector_,
		Eigen::MatrixXf &	_p_matrix_,
		std::vector< int > &	matched_ids,
		std::vector< Eigen::Vector2f > &	matched_cone_positions,
		std::vector< Eigen::Vector2f > &	new_features,
		ObservationModel *	observation_model
	)		const

overridevirtual

normalized distance gate (closest unmatched landmark)

Associate the observed landmarks to the expected landmarks and update the state vector and the covariance matrix

Parameters

perception_map	The observed landmarks
_x_vector_	The state vector
_p_matrix_	The covariance matrix
matched_ids	Vector in which the ids of the matched landmarks will be placed
matched_cone_positions	Vector in which the positions of the matched landmarks will be placed
new_features	Vector in which the positions of the new landmarks (unmatched landmarks) will be placed
observation_model	The observation model

Returns: int Always 0

Implements DataAssociationModel.

Definition at line 27 of file data_association.cpp.

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Member Data Documentation

◆ association_gate_

float MaxLikelihood::association_gate_ = 4.991f

static

Definition at line 75 of file data_association.hpp.

◆ new_landmark_gate_

float MaxLikelihood::new_landmark_gate_ = 20.0f

static

normalized innovation squared gate

Definition at line 76 of file data_association.hpp.

The documentation for this class was generated from the following files:

src/ekf_state_est/include/kalman_filter/data_association.hpp
src/ekf_state_est/src/kalman_filter/data_association.cpp

Public Member Functions

Static Public Attributes

Additional Inherited Members