cloud_kdtree::KdTreeFLANN Class Reference

#include <kdtree_flann.h>

Inheritance diagram for cloud_kdtree::KdTreeFLANN:

Public Member Functions
	KdTreeFLANN (const sensor_msgs::PointCloud &points, const std::vector< int > &indices)
	Constructor for KdTree.
	KdTreeFLANN (const sensor_msgs::PointCloud &points)
	Constructor for KdTree.
virtual void	nearestKSearch (int index, int k, std::vector< int > &k_indices, std::vector< float > &k_distances)
	Search for k-nearest neighbors for the given query point.
virtual void	nearestKSearch (const sensor_msgs::PointCloud &points, int index, int k, std::vector< int > &k_indices, std::vector< float > &k_distances)
	Search for k-nearest neighbors for the given query point.
virtual void	nearestKSearch (const geometry_msgs::Point32 &p_q, int k, std::vector< int > &k_indices, std::vector< float > &k_distances)
	Search for k-nearest neighbors for the given query point.
virtual bool	radiusSearch (int index, double radius, std::vector< int > &k_indices, std::vector< float > &k_distances, int max_nn=INT_MAX)
	Search for all the nearest neighbors of the query point in a given radius.
virtual bool	radiusSearch (const sensor_msgs::PointCloud &points, int index, double radius, std::vector< int > &k_indices, std::vector< float > &k_distances, int max_nn=INT_MAX)
	Search for all the nearest neighbors of the query point in a given radius.
virtual bool	radiusSearch (const geometry_msgs::Point32 &p_q, double radius, std::vector< int > &k_indices, std::vector< float > &k_distances, int max_nn=INT_MAX)
	Search for all the nearest neighbors of the query point in a given radius.
virtual	~KdTreeFLANN ()
	Destructor for KdTree. Deletes all allocated data arrays and destroys the kd-tree structures.
Private Member Functions
int	convertCloudToArray (const sensor_msgs::PointCloud &ros_cloud, const std::vector< int > &indices)
	Converts a ROS PointCloud message with a given set of indices to the internal ANN point array representation. Returns the number of points.
int	convertCloudToArray (const sensor_msgs::PointCloud &ros_cloud)
	Converts a ROS PointCloud message to the internal ANN point array representation. Returns the number of points.
Private Attributes
int	dim_
	Tree dimensionality (i.e. the number of dimensions per point).
FLANNParameters	flann_param_
	A pointer to a FL-ANN parameter structure.
FLANN_INDEX	index_id_
	A FL-ANN type index reference.
boost::mutex	m_lock_
int	nr_points_
	Number of points in the tree.
float *	points_
	Internal pointer to data.

Detailed Description

Definition at line 46 of file kdtree_flann.h.

Constructor & Destructor Documentation

cloud_kdtree::KdTreeFLANN::KdTreeFLANN ( const sensor_msgs::PointCloud & points ) [inline]

Constructor for KdTree.

Parameters:

points

the ROS point cloud data array

Definition at line 54 of file kdtree_flann.h.

cloud_kdtree::KdTreeFLANN::KdTreeFLANN	(	const sensor_msgs::PointCloud &	points,
		const std::vector< int > &	indices
	)			`[inline]`

Constructor for KdTree.

Note:: ATTENTION: This method breaks the 1-1 mapping between the indices returned using getNeighborsIndices and the ones from the points message ! When using this method, make sure to get the underlying point data using the getPoint method

Parameters:

	points	the ROS point cloud data array
	indices	the point cloud indices

Definition at line 92 of file kdtree_flann.h.

virtual cloud_kdtree::KdTreeFLANN::~KdTreeFLANN ( ) [inline, virtual]

Destructor for KdTree. Deletes all allocated data arrays and destroys the kd-tree structures.

Definition at line 122 of file kdtree_flann.h.

Member Function Documentation

int cloud_kdtree::KdTreeFLANN::convertCloudToArray	(	const sensor_msgs::PointCloud &	ros_cloud,
		const std::vector< int > &	indices
	)			`[private]`

Converts a ROS PointCloud message with a given set of indices to the internal ANN point array representation. Returns the number of points.

Note:: ATTENTION: This method breaks the 1-1 mapping between the indices returned using getNeighborsIndices and the ones from the ros_cloud message ! When using this method, make sure to get the underlying point data using the getPoint method

Parameters:

	ros_cloud	the ROS PointCloud message
	indices	the point cloud indices

Definition at line 239 of file kdtree_flann.cpp.

int cloud_kdtree::KdTreeFLANN::convertCloudToArray ( const sensor_msgs::PointCloud & ros_cloud ) [private]

Converts a ROS PointCloud message to the internal ANN point array representation. Returns the number of points.

Parameters:

ros_cloud

the ROS PointCloud message

Definition at line 204 of file kdtree_flann.cpp.

virtual void cloud_kdtree::KdTreeFLANN::nearestKSearch	(	int	index,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances
	)			`[inline, virtual]`

Search for k-nearest neighbors for the given query point.

Parameters:

	index	the index in points representing the query point
	k	the number of neighbors to search for
	k_indices	the resultant point indices
	k_distances	the resultant point distances

Implements cloud_kdtree::KdTree.

Definition at line 147 of file kdtree_flann.h.

void cloud_kdtree::KdTreeFLANN::nearestKSearch	(	const sensor_msgs::PointCloud &	points,
		int	index,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances
	)			`[virtual]`

Search for k-nearest neighbors for the given query point.

Parameters:

	points	the point cloud data
	index	the index in points representing the query point
	k	the number of neighbors to search for
	k_indices	the resultant point indices
	k_distances	the resultant point distances

Implements cloud_kdtree::KdTree.

Definition at line 97 of file kdtree_flann.cpp.

void cloud_kdtree::KdTreeFLANN::nearestKSearch	(	const geometry_msgs::Point32 &	p_q,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances
	)			`[virtual]`

Search for k-nearest neighbors for the given query point.

Parameters:

	p_q	the given query point
	k	the number of neighbors to search for
	k_indices	the resultant point indices
	k_distances	the resultant point distances

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0 12 198 1 2 125 26 278 42 248 0 12 198 1 18 132 10 197 16 9 0 12 198 1 18 132 10 197 16 9 0 12 198 1 18 132 10 197 16 9

Implements cloud_kdtree::KdTree.

Definition at line 43 of file kdtree_flann.cpp.

virtual bool cloud_kdtree::KdTreeFLANN::radiusSearch	(	int	index,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances,
		int	max_nn = `INT_MAX`
	)			`[inline, virtual]`

Search for all the nearest neighbors of the query point in a given radius.

Parameters:

	index	the index in points representing the query point
	radius	the radius of the sphere bounding all of p_q's neighbors
	k_indices	the resultant point indices
	k_distances	the resultant point distances
	max_nn	if given, bounds the maximum returned neighbors to this value

Implements cloud_kdtree::KdTree.

Definition at line 170 of file kdtree_flann.h.

bool cloud_kdtree::KdTreeFLANN::radiusSearch	(	const sensor_msgs::PointCloud &	points,
		int	index,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances,
		int	max_nn = `INT_MAX`
	)			`[virtual]`

Search for all the nearest neighbors of the query point in a given radius.

Parameters:

	points	the point cloud data
	index	the index in points representing the query point
	radius	the radius of the sphere bounding all of p_q's neighbors
	k_indices	the resultant point indices
	k_distances	the resultant point distances
	max_nn	if given, bounds the maximum returned neighbors to this value

Implements cloud_kdtree::KdTree.

Definition at line 166 of file kdtree_flann.cpp.

bool cloud_kdtree::KdTreeFLANN::radiusSearch	(	const geometry_msgs::Point32 &	p_q,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances,
		int	max_nn = `INT_MAX`
	)			`[virtual]`

Search for all the nearest neighbors of the query point in a given radius.

Parameters:

	p_q	the given query point
	radius	the radius of the sphere bounding all of p_q's neighbors
	k_indices	the resultant point indices
	k_distances	the resultant point distances
	max_nn	if given, bounds the maximum returned neighbors to this value