cloud_kdtree::KdTreeANN Class Reference

#include <kdtree_ann.h>

Inheritance diagram for cloud_kdtree::KdTreeANN:

Public Member Functions
	KdTreeANN (const sensor_msgs::PointCloud &points, const std::vector< int > &indices)
	Constructor for KdTree.
	KdTreeANN (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	~KdTreeANN ()
	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
ANNkd_tree *	ann_kd_tree_
	The ANN kd tree object.
double	bucket_size_
	Internal tree bucket size.
int	dim_
	Tree dimensionality (i.e. the number of dimensions per point).
boost::mutex	m_lock_
int	nr_points_
	Number of points in the tree.
ANNpointArray	points_
	Internal pointer to data.

Detailed Description

Definition at line 44 of file kdtree_ann.h.

Constructor & Destructor Documentation

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

Constructor for KdTree.

Parameters:

points

the ROS point cloud data array

Definition at line 52 of file kdtree_ann.h.

cloud_kdtree::KdTreeANN::KdTreeANN	(	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 81 of file kdtree_ann.h.

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

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

Definition at line 104 of file kdtree_ann.h.

Member Function Documentation

int cloud_kdtree::KdTreeANN::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 209 of file kdtree_ann.cpp.

int cloud_kdtree::KdTreeANN::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 174 of file kdtree_ann.cpp.

virtual void cloud_kdtree::KdTreeANN::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 131 of file kdtree_ann.h.

void cloud_kdtree::KdTreeANN::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 70 of file kdtree_ann.cpp.

void cloud_kdtree::KdTreeANN::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

Implements cloud_kdtree::KdTree.

Definition at line 45 of file kdtree_ann.cpp.

virtual bool cloud_kdtree::KdTreeANN::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 157 of file kdtree_ann.h.

bool cloud_kdtree::KdTreeANN::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 138 of file kdtree_ann.cpp.

bool cloud_kdtree::KdTreeANN::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