Adaptive Motion Planning Based on Vehicle Characteristics and Regulations for Off-Road UGVs

Yonghoon Ji, Yusuke Tanaka, Yusuke Tamura, Mai Kimura, Atsushi Umemura, Yoshiharu Kaneshima, Hiroki Murakami, Atsushi Yamashita, Hajime Asama

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)


In this paper, we propose a novel motion planning method for off-road unmanned ground vehicles, based on three-dimensional (3-D) terrain map information. Previous studies on the motion planning of a vehicle traveling on rough terrain dealt only with a relatively small environment. Furthermore, unique vehicle characteristics were not considered, and it was also impossible to incorporate regulations, such as maintaining driving speed and suppressing posture change. The proposed method enables vehicles to adaptively generate a path by considering vehicle characteristics and the regulations, in a large-scale environment, with rough terrain. A random sampling based scheme was applied to carrying out global path planning, based on a 3-D environmental model. Experimental results showed that the proposed off-road motion planner could generate an appropriate path, which satisfies vehicle characteristics and predefined regulations.

Original languageEnglish
Article number8466595
Pages (from-to)599-611
Number of pages13
JournalIEEE Transactions on Industrial Informatics
Issue number1
Publication statusPublished - 2019 Jan
Externally publishedYes


  • Autonomous navigation
  • field robots
  • motion planning
  • unmanned ground vehicle (UGV)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering


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