cloud_kdtree::KdTree Class Reference

#include <kdtree.h>

Inheritance diagram for cloud_kdtree::KdTree:

[legend]

List of all members.

Public Member Functions
	KdTree (const sensor_msgs::PointCloud &points, const std::vector< int > &indices)
	Constructor for KdTree.
	KdTree (const sensor_msgs::PointCloud &points)
	Constructor for KdTree.
	KdTree ()
	Empty constructor for KdTree. Sets some internal values to their defaults.
virtual void	nearestKSearch (int index, int k, std::vector< int > &k_indices, std::vector< float > &k_distances)=0
virtual void	nearestKSearch (const sensor_msgs::PointCloud &points, int index, int k, std::vector< int > &k_indices, std::vector< float > &k_distances)=0
virtual void	nearestKSearch (const geometry_msgs::Point32 &p_q, int k, std::vector< int > &k_indices, std::vector< float > &k_distances)=0
virtual bool	radiusSearch (int index, double radius, std::vector< int > &k_indices, std::vector< float > &k_distances, int max_nn=INT_MAX)=0
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)=0
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)=0
virtual	~KdTree ()
	Destructor for KdTree. Deletes all allocated data arrays and destroys the kd-tree structures.
Protected Attributes
double	epsilon_
	Epsilon precision (error bound) for nearest neighbors searches.

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Detailed Description

Definition at line 42 of file kdtree.h.

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Constructor & Destructor Documentation

cloud_kdtree::KdTree::KdTree

(

)

[inline]

Empty constructor for KdTree. Sets some internal values to their defaults.

Definition at line 49 of file kdtree.h.

cloud_kdtree::KdTree::KdTree

(

const sensor_msgs::PointCloud &

points

)

Constructor for KdTree.

Parameters:

points

the ROS point cloud data array

cloud_kdtree::KdTree::KdTree	(	const sensor_msgs::PointCloud &	points,
		const std::vector< int > &	indices
	)

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

virtual cloud_kdtree::KdTree::~KdTree

(

)

[inline, virtual]

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

Definition at line 72 of file kdtree.h.

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Member Function Documentation

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

Implemented in cloud_kdtree::KdTreeANN.

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

Implemented in cloud_kdtree::KdTreeANN.

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

Implemented in cloud_kdtree::KdTreeANN.

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

Implemented in cloud_kdtree::KdTreeANN.

virtual bool cloud_kdtree::KdTree::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
	)			[pure virtual]

Implemented in cloud_kdtree::KdTreeANN.

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

Implemented in cloud_kdtree::KdTreeANN.

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Member Data Documentation

double cloud_kdtree::KdTree::epsilon_ [protected]

Epsilon precision (error bound) for nearest neighbors searches.

Definition at line 88 of file kdtree.h.

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

• kdtree.h