LiDAR-based Road Intrusion Detection Technology forAutonomous-rail Rapid Tram

In order to ensure the operation safety of autonomous-rail rapid tram and improve the efficiency and robustness of road intrusion detection, a road intrusion detection technology based on multi-LiDAR was proposed in this paper. ROS framework is adopted to collect and fuse multiple radar data in orde...

Full description

Saved in:
Bibliographic Details
Main Authors: LONG Teng, LIU Sisi, HU Yunqing, LI Xiaoguang, YUAN Xiwen, PAN Wenbo, LUO Yiping, YU Wentian
Format: Article
Language:zho
Published: Editorial Office of Control and Information Technology 2020-01-01
Series:Kongzhi Yu Xinxi Jishu
Subjects:
Online Access:http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2020.04.014
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In order to ensure the operation safety of autonomous-rail rapid tram and improve the efficiency and robustness of road intrusion detection, a road intrusion detection technology based on multi-LiDAR was proposed in this paper. ROS framework is adopted to collect and fuse multiple radar data in order to obtain low complexity point cloud data without overlapping region. Point cloud data is de-noised by multi-key point iteration and multi-generation model using Ground Plane Fitting algorithm, and point cloud data with low noise and easy segmentation is returned. By using Scan Line Run algorithm and 3D structure of point cloud data, non-repetitive tagging is performed from top to bottom to return the location, size and points of road intrusions. Several common road intrusions are extracted and trained, and classified based on the previously tagged intrusions. Experimental results show that the proposed method has good robustness and accuracy in recognition and classification.
ISSN:2096-5427