cloud_kdtree::KdTreeFLANN Class Reference

#include <kdtree_flann.h>

Inheritance diagram for cloud_kdtree::KdTreeFLANN:

List of all members.

Public Member Functions
	KdTreeFLANN (const sensor_msgs::PointCloud &points)
	Constructor for KdTree.
	KdTreeFLANN (const sensor_msgs::PointCloud &points, const std::vector< int > &indices)
	Constructor for KdTree.
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 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 (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 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 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 (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	~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)
	Converts a ROS PointCloud message to the internal ANN point array representation. Returns the number of points.
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.
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.

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Detailed Description

Definition at line 46 of file kdtree_flann.h.

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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.

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Member Function Documentation

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 206 of file kdtree_flann.cpp.

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 241 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

0 12 198 1 127 18 132 10 11 197

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 45 of file kdtree_flann.cpp.

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 99 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.

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

Implements cloud_kdtree::KdTree.

Definition at line 127 of file kdtree_flann.cpp.

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 168 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.

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Member Data Documentation

int cloud_kdtree::KdTreeFLANN::dim_ [private]

Tree dimensionality (i.e. the number of dimensions per point)

Definition at line 220 of file kdtree_flann.h.

FLANNParameters cloud_kdtree::KdTreeFLANN::flann_param_ [private]

A pointer to a FL-ANN parameter structure.

Definition at line 212 of file kdtree_flann.h.

FLANN_INDEX cloud_kdtree::KdTreeFLANN::index_id_ [private]

A FL-ANN type index reference.

Definition at line 209 of file kdtree_flann.h.

boost::mutex cloud_kdtree::KdTreeFLANN::m_lock_ [private]

Definition at line 206 of file kdtree_flann.h.

int cloud_kdtree::KdTreeFLANN::nr_points_ [private]

Number of points in the tree.

Definition at line 218 of file kdtree_flann.h.

float* cloud_kdtree::KdTreeFLANN::points_ [private]

Internal pointer to data.

Definition at line 215 of file kdtree_flann.h.

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

• kdtree_flann.h
• kdtree_flann.cpp