MovingLeastSquares represents a nodelet using the MovingLeastSquares implementation. The type of the output is the same as the input, it only smooths the XYZ coordinates according to the parameters. Normals are estimated at each point as well and published on a separate topic. More...

#include <moving_least_squares.h>

Inheritance diagram for pcl_ros::MovingLeastSquares:

[legend]

List of all members.

Protected Member Functions
void	config_callback (MLSConfig &config, uint32_t level)
	Dynamic reconfigure callback.
Protected Attributes
double	gaussian_parameter_
	How 'flat' should the neighbor weighting gaussian be (the smaller, the more local the fit).
int	polynomial_order_
	The order of the polynomial to be fit.
double	search_radius_
	The nearest neighbors search radius for each point.
int	spatial_locator_type_
	Parameter for the spatial locator tree. By convention, the values represent: 0: ANN (Approximate Nearest Neigbor library) kd-tree 1: FLANN (Fast Library for Approximate Nearest Neighbors) kd-tree 2: Organized spatial dataset index.
boost::shared_ptr < dynamic_reconfigure::Server < MLSConfig > >	srv_
	Pointer to a dynamic reconfigure service.
message_filters::Subscriber < PointCloudIn >	sub_surface_filter_
	The surface PointCloud subscriber filter.
PointCloudInConstPtr	surface_
	An input point cloud describing the surface that is to be used for nearest neighbors estimation.
KdTreePtr	tree_
	A pointer to the spatial search object.
bool	use_polynomial_fit_
	The number of K nearest neighbors to use for each point.
Private Types
typedef pcl::KdTree< PointIn >	KdTree
typedef pcl::KdTree< PointIn >::Ptr	KdTreePtr
typedef pcl::PointCloud < NormalOut >	NormalCloudOut
typedef pcl::PointNormal	NormalOut
typedef pcl::PointCloud< PointIn >	PointCloudIn
typedef PointCloudIn::ConstPtr	PointCloudInConstPtr
typedef PointCloudIn::Ptr	PointCloudInPtr
typedef pcl::PointXYZ	PointIn
Private Member Functions
void	input_indices_callback (const PointCloudInConstPtr &cloud, const PointIndicesConstPtr &indices)
	Input point cloud callback.
virtual void	onInit ()
	Nodelet initialization routine.
Private Attributes
pcl::MovingLeastSquares < PointIn, NormalOut >	impl_
	The PCL implementation used.
ros::Publisher	pub_normals_
	The output PointCloud (containing the normals) publisher.
ros::Subscriber	sub_input_
	The input PointCloud subscriber.
boost::shared_ptr < message_filters::Synchronizer < sync_policies::ApproximateTime < PointCloudIn, PointIndices > > >	sync_input_indices_a_
boost::shared_ptr < message_filters::Synchronizer < sync_policies::ExactTime < PointCloudIn, PointIndices > > >	sync_input_indices_e_
	Synchronized input, and indices.

Detailed Description

MovingLeastSquares represents a nodelet using the MovingLeastSquares implementation. The type of the output is the same as the input, it only smooths the XYZ coordinates according to the parameters. Normals are estimated at each point as well and published on a separate topic.

Author:: Radu Bogdan Rusu, Zoltan-Csaba Marton

Definition at line 59 of file moving_least_squares.h.

Member Typedef Documentation

typedef pcl::KdTree<PointIn> pcl_ros::MovingLeastSquares::KdTree [private]

Definition at line 69 of file moving_least_squares.h.

typedef pcl::KdTree<PointIn>::Ptr pcl_ros::MovingLeastSquares::KdTreePtr [private]

Definition at line 70 of file moving_least_squares.h.

typedef pcl::PointCloud<NormalOut> pcl_ros::MovingLeastSquares::NormalCloudOut [private]

Definition at line 67 of file moving_least_squares.h.

typedef pcl::PointNormal pcl_ros::MovingLeastSquares::NormalOut [private]

Definition at line 62 of file moving_least_squares.h.

typedef pcl::PointCloud<PointIn> pcl_ros::MovingLeastSquares::PointCloudIn [private]

Definition at line 64 of file moving_least_squares.h.

typedef PointCloudIn::ConstPtr pcl_ros::MovingLeastSquares::PointCloudInConstPtr [private]

Definition at line 66 of file moving_least_squares.h.

typedef PointCloudIn::Ptr pcl_ros::MovingLeastSquares::PointCloudInPtr [private]

Definition at line 65 of file moving_least_squares.h.

typedef pcl::PointXYZ pcl_ros::MovingLeastSquares::PointIn [private]

Definition at line 61 of file moving_least_squares.h.

Member Function Documentation

void pcl_ros::MovingLeastSquares::config_callback	(	MLSConfig &	config,
		uint32_t	level
	)		`[protected]`

Dynamic reconfigure callback.

Parameters:

config	the config object
level	the dynamic reconfigure level

Definition at line 174 of file moving_least_squares.cpp.

void pcl_ros::MovingLeastSquares::input_indices_callback	(	const PointCloudInConstPtr &	cloud,
		const PointIndicesConstPtr &	indices
	)		`[private]`

Input point cloud callback.

Parameters:

cloud	the pointer to the input point cloud
indices	the pointer to the input point cloud indices

DEBUG

Definition at line 108 of file moving_least_squares.cpp.

void pcl_ros::MovingLeastSquares::onInit ( ) [private, virtual]

Nodelet initialization routine.

Reimplemented from pcl_ros::PCLNodelet.

Definition at line 43 of file moving_least_squares.cpp.

Member Data Documentation

double pcl_ros::MovingLeastSquares::gaussian_parameter_ [protected]

How 'flat' should the neighbor weighting gaussian be (the smaller, the more local the fit).

Definition at line 92 of file moving_least_squares.h.

pcl::MovingLeastSquares<PointIn, NormalOut> pcl_ros::MovingLeastSquares::impl_ [private]

The PCL implementation used.

Definition at line 128 of file moving_least_squares.h.

int pcl_ros::MovingLeastSquares::polynomial_order_ [protected]

The order of the polynomial to be fit.

Definition at line 89 of file moving_least_squares.h.

ros::Publisher pcl_ros::MovingLeastSquares::pub_normals_ [private]

The output PointCloud (containing the normals) publisher.

Definition at line 134 of file moving_least_squares.h.

double pcl_ros::MovingLeastSquares::search_radius_ [protected]

The nearest neighbors search radius for each point.

Definition at line 80 of file moving_least_squares.h.

int pcl_ros::MovingLeastSquares::spatial_locator_type_ [protected]

Parameter for the spatial locator tree. By convention, the values represent: 0: ANN (Approximate Nearest Neigbor library) kd-tree 1: FLANN (Fast Library for Approximate Nearest Neighbors) kd-tree 2: Organized spatial dataset index.

Definition at line 103 of file moving_least_squares.h.

boost::shared_ptr<dynamic_reconfigure::Server<MLSConfig> > pcl_ros::MovingLeastSquares::srv_ [protected]

Pointer to a dynamic reconfigure service.

Definition at line 106 of file moving_least_squares.h.

ros::Subscriber pcl_ros::MovingLeastSquares::sub_input_ [private]

The input PointCloud subscriber.

Definition at line 131 of file moving_least_squares.h.

message_filters::Subscriber<PointCloudIn> pcl_ros::MovingLeastSquares::sub_surface_filter_ [protected]

The surface PointCloud subscriber filter.

Definition at line 96 of file moving_least_squares.h.

PointCloudInConstPtr pcl_ros::MovingLeastSquares::surface_ [protected]

An input point cloud describing the surface that is to be used for nearest neighbors estimation.