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>
Protected Member Functions | |
void | config_callback (MLSConfig &config, uint32_t level) |
Dynamic reconfigure callback. More... | |
virtual void | onInit () |
Nodelet initialization routine. More... | |
virtual void | subscribe () |
LazyNodelet connection routine. More... | |
virtual void | unsubscribe () |
Protected Member Functions inherited from pcl_ros::PCLNodelet | |
bool | isValid (const ModelCoefficientsConstPtr &, const std::string &="model") |
Test whether a given ModelCoefficients message is "valid" (i.e., has values). More... | |
bool | isValid (const PointCloud2::ConstPtr &cloud, const std::string &topic_name="input") |
Test whether a given PointCloud message is "valid" (i.e., has points, and width and height are non-zero). More... | |
bool | isValid (const PointCloudConstPtr &cloud, const std::string &topic_name="input") |
Test whether a given PointCloud message is "valid" (i.e., has points, and width and height are non-zero). More... | |
bool | isValid (const PointIndicesConstPtr &, const std::string &="indices") |
Test whether a given PointIndices message is "valid" (i.e., has values). More... | |
Protected Member Functions inherited from nodelet_topic_tools::NodeletLazy | |
ros::Publisher | advertise (ros::NodeHandle &nh, std::string topic, int queue_size, bool latch=false) |
virtual void | connectionCallback (const ros::SingleSubscriberPublisher &pub) |
virtual void | onInitPostProcess () |
virtual void | warnNeverSubscribedCallback (const ros::WallTimerEvent &event) |
Protected Member Functions inherited from nodelet::Nodelet | |
ros::CallbackQueueInterface & | getMTCallbackQueue () const |
ros::NodeHandle & | getMTNodeHandle () const |
ros::NodeHandle & | getMTPrivateNodeHandle () const |
const V_string & | getMyArgv () const |
const std::string & | getName () const |
ros::NodeHandle & | getNodeHandle () const |
ros::NodeHandle & | getPrivateNodeHandle () const |
const M_string & | getRemappingArgs () const |
ros::CallbackQueueInterface & | getSTCallbackQueue () const |
std::string | getSuffixedName (const std::string &suffix) const |
Protected Attributes | |
double | gaussian_parameter_ |
How 'flat' should the neighbor weighting gaussian be (the smaller, the more local the fit). More... | |
int | polynomial_order_ |
The order of the polynomial to be fit. More... | |
double | search_radius_ |
The nearest neighbors search radius for each point. More... | |
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. More... | |
boost::shared_ptr< dynamic_reconfigure::Server< MLSConfig > > | srv_ |
Pointer to a dynamic reconfigure service. More... | |
message_filters::Subscriber< PointCloudIn > | sub_surface_filter_ |
The surface PointCloud subscriber filter. More... | |
PointCloudInConstPtr | surface_ |
An input point cloud describing the surface that is to be used for nearest neighbors estimation. More... | |
KdTreePtr | tree_ |
A pointer to the spatial search object. More... | |
bool | use_polynomial_fit_ |
The number of K nearest neighbors to use for each point. More... | |
Protected Attributes inherited from pcl_ros::PCLNodelet | |
bool | approximate_sync_ |
True if we use an approximate time synchronizer versus an exact one (false by default). More... | |
bool | latched_indices_ |
Set to true if the indices topic is latched. More... | |
int | max_queue_size_ |
The maximum queue size (default: 3). More... | |
ros::Publisher | pub_output_ |
The output PointCloud publisher. More... | |
message_filters::Subscriber< PointIndices > | sub_indices_filter_ |
The message filter subscriber for PointIndices. More... | |
message_filters::Subscriber< PointCloud > | sub_input_filter_ |
The message filter subscriber for PointCloud2. More... | |
tf::TransformListener | tf_listener_ |
TF listener object. More... | |
bool | use_indices_ |
Set to true if point indices are used. More... | |
Protected Attributes inherited from nodelet_topic_tools::NodeletLazy | |
boost::mutex | connection_mutex_ |
ConnectionStatus | connection_status_ |
bool | ever_subscribed_ |
bool | lazy_ |
boost::shared_ptr< ros::NodeHandle > | nh_ |
boost::shared_ptr< ros::NodeHandle > | pnh_ |
std::vector< ros::Publisher > | publishers_ |
ros::WallTimer | timer_ever_subscribed_ |
bool | verbose_connection_ |
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 boost::shared_ptr< const PointCloudIn > | PointCloudInConstPtr |
typedef boost::shared_ptr< PointCloudIn > | PointCloudInPtr |
typedef pcl::PointXYZ | PointIn |
Private Member Functions | |
void | input_indices_callback (const PointCloudInConstPtr &cloud, const PointIndicesConstPtr &indices) |
Input point cloud callback. More... | |
Private Attributes | |
pcl::MovingLeastSquares< PointIn, NormalOut > | impl_ |
The PCL implementation used. More... | |
ros::Publisher | pub_normals_ |
The output PointCloud (containing the normals) publisher. More... | |
ros::Subscriber | sub_input_ |
The input PointCloud subscriber. More... | |
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. More... | |
Additional Inherited Members | |
Public Types inherited from pcl_ros::PCLNodelet | |
typedef pcl::IndicesConstPtr | IndicesConstPtr |
typedef pcl::IndicesPtr | IndicesPtr |
typedef pcl_msgs::ModelCoefficients | ModelCoefficients |
typedef ModelCoefficients::ConstPtr | ModelCoefficientsConstPtr |
typedef ModelCoefficients::Ptr | ModelCoefficientsPtr |
typedef pcl::PointCloud< pcl::PointXYZ > | PointCloud |
typedef sensor_msgs::PointCloud2 | PointCloud2 |
typedef boost::shared_ptr< const PointCloud > | PointCloudConstPtr |
typedef boost::shared_ptr< PointCloud > | PointCloudPtr |
typedef pcl_msgs::PointIndices | PointIndices |
typedef PointIndices::ConstPtr | PointIndicesConstPtr |
typedef PointIndices::Ptr | PointIndicesPtr |
Public Member Functions inherited from pcl_ros::PCLNodelet | |
PCLNodelet () | |
Empty constructor. More... | |
Public Member Functions inherited from nodelet_topic_tools::NodeletLazy | |
NodeletLazy () | |
Public Member Functions inherited from nodelet::Nodelet | |
void | init (const std::string &name, const M_string &remapping_args, const V_string &my_argv, ros::CallbackQueueInterface *st_queue=NULL, ros::CallbackQueueInterface *mt_queue=NULL) |
Nodelet () | |
virtual | ~Nodelet () |
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.
Definition at line 60 of file moving_least_squares.h.
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Definition at line 70 of file moving_least_squares.h.
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Definition at line 71 of file moving_least_squares.h.
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Definition at line 68 of file moving_least_squares.h.
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Definition at line 63 of file moving_least_squares.h.
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Definition at line 65 of file moving_least_squares.h.
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Definition at line 67 of file moving_least_squares.h.
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Definition at line 66 of file moving_least_squares.h.
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Definition at line 62 of file moving_least_squares.h.
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Dynamic reconfigure callback.
config | the config object |
level | the dynamic reconfigure level |
Definition at line 192 of file moving_least_squares.cpp.
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Input point cloud callback.
cloud | the pointer to the input point cloud |
indices | the pointer to the input point cloud indices |
DEBUG
Definition at line 126 of file moving_least_squares.cpp.
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protectedvirtual |
Nodelet initialization routine.
Reimplemented from pcl_ros::PCLNodelet.
Definition at line 42 of file moving_least_squares.cpp.
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LazyNodelet connection routine.
Reimplemented from pcl_ros::PCLNodelet.
Definition at line 81 of file moving_least_squares.cpp.
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protectedvirtual |
Reimplemented from pcl_ros::PCLNodelet.
Definition at line 113 of file moving_least_squares.cpp.
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How 'flat' should the neighbor weighting gaussian be (the smaller, the more local the fit).
Definition at line 93 of file moving_least_squares.h.
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The PCL implementation used.
Definition at line 133 of file moving_least_squares.h.
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The order of the polynomial to be fit.
Definition at line 90 of file moving_least_squares.h.
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The output PointCloud (containing the normals) publisher.
Definition at line 139 of file moving_least_squares.h.
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The nearest neighbors search radius for each point.
Definition at line 81 of file moving_least_squares.h.
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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 104 of file moving_least_squares.h.
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Pointer to a dynamic reconfigure service.
Definition at line 107 of file moving_least_squares.h.
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The input PointCloud subscriber.
Definition at line 136 of file moving_least_squares.h.
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The surface PointCloud subscriber filter.
Definition at line 97 of file moving_least_squares.h.
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An input point cloud describing the surface that is to be used for nearest neighbors estimation.
Definition at line 75 of file moving_least_squares.h.
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Definition at line 143 of file moving_least_squares.h.
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Synchronized input, and indices.
Definition at line 142 of file moving_least_squares.h.
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A pointer to the spatial search object.
Definition at line 78 of file moving_least_squares.h.
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The number of K nearest neighbors to use for each point.
Whether to use a polynomial fit.
Definition at line 87 of file moving_least_squares.h.