UGV autonomous driving system design for unstructed environment

Jingqin Zhang, Jun Hou, Jinwen Hu, Chunhui Zhao, Zhao Xu, Changwei Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Autonomous Unmanned Ground Vehicle (UGV) in complex environments is currently a popular research area. Due to the limitation of sensors and abundant environmental information, it is difficult for UGV to obtain their own status and environmental information in real time. This article proposes an autonomous UGV system based on LiDAR and camera in GNSS-denied scenarios. The camera and LiDAR are used to detect various obstacles in the environment separately. Then, we propose an obstacle detection fusion strategy, which eliminates false detection and improves accuracy of target detection. Finally the real-world experiments show that, based on our multi-sensor fusion detection algorithm, UGV can move autonomously and safely in unstructured environment, which consists of convex and concave obstacles.

Original languageEnglish
Title of host publicationProceedings of the 40th Chinese Control Conference, CCC 2021
EditorsChen Peng, Jian Sun
PublisherIEEE Computer Society
Pages4157-4162
Number of pages6
ISBN (Electronic)9789881563804
DOIs
StatePublished - 26 Jul 2021
Event40th Chinese Control Conference, CCC 2021 - Shanghai, China
Duration: 26 Jul 202128 Jul 2021

Publication series

NameChinese Control Conference, CCC
Volume2021-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference40th Chinese Control Conference, CCC 2021
Country/TerritoryChina
CityShanghai
Period26/07/2128/07/21

Keywords

  • Automation
  • Obstacle detection
  • Sensor fusion
  • SLAM

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