Shape Estimation

L-shape fitting implementation of the paper:

@conference{Zhang-2017-26536,
author = {Xiao Zhang and Wenda Xu and Chiyu Dong and John M. Dolan},
title = {Efficient L-Shape Fitting for Vehicle Detection Using Laser Scanners},
booktitle = {2017 IEEE Intelligent Vehicles Symposium},
year = {2017},
month = {June},
keywords = {autonomous driving, laser scanner, perception, segmentation},
}

How to launch

From RTM

Computing tab -> Detection -> lidar_detector -> lidar_shape_estimation

Configure parameters using the [app] button.

From the command line

From a sourced command line: roslaunch lidar_shape_estimation shape_estimation_clustering.launch

Launch files also include the visualization node.

Requirements

1. LiDAR data segmented.
2. Objects

Parameters

Parameter	Type	Description	Default
input	String	Topic name containing the objects detected by the Lidar in 3D space.	/detection/lidar_detector/objects
output	String	Topic name containing the objects with the shape estimated in 3D space.	/detection/lidar_shape_estimation/objects

Usage example

1. Launch a ground filter algorithm from the Points Preprocessor section in the Sensing tab. (adjust the parameters to your vehicle setup).
2. Launch a Lidar Detector from the Computing tab.
3. Launch this node.

Node info

Node [/lidar_shape_estimation]
Publications:
 * /detection/shape_estimation/objects [autoware_perception_msgs/DetectedObjectArray]

Subscriptions:
 * /detection/lidar_detector/objects [autoware_perception_msgs/DetectedObjectArray]

-------------------------
Node [/detection/shape_estimation/shape_estimation_visualization]
Publications:
 * /detection/shape_estimation/objects_markers [visualization_msgs/MarkerArray]

Subscriptions:
 * /detection/shape_estimation/objects [autoware_perception_msgs/DetectedObjectArray]