EuclideanClustering

What Is This

Segment pointcloud based euclidean metrics, which is based on pcl::EuclideanClusterExtraction. This nodelet has topic interface and service interface.

The result of clustering is published as jsk_recognition_msgs/ClusterPointIndices.

If the number of the cluster is not changed across different frames, EuclideanClustering tries to track the segment.

Subscribing Topics

• ~input (sensor_msgs/PointCloud2):

  input pointcloud.

Publishing Topics

• ~output (jsk_recognition_msgs/ClusterPointIndices):

  Result of clustering.

• ~cluster_num (jsk_recognition_msgs/Int32Stamped):

  The number of clusters.

Advertising Services

• ~euclidean_clustering (jsk_pcl_ros/EuclideanSegment):

  Service interface to segment clusters.

sensor_msgs/PointCloud2 input
float32 tolerance
---
sensor_msgs/PointCloud2[] output

Parameters

• ~tolerance (Double, default: 0.02):

  Max distance for the points to be regarded as same cluster.

• ~label_tracking_tolerance (Double, default: 0.2)

  Max distance to track the cluster between different frames.

• ~max_size (Integer, default: 25000)

  The maximum number of the points of one cluster.

• ~min_size (Integer, default: 20)

  The minimum number of the points of one cluster.

Sample

Plug the depth sensor which can be launched by openni.launch and run the below command.

roslaunch jsk_pcl_ros euclidean_segmentation.launch