Traversability-based Trajectory Planning with Quasi-Dynamic Vehicle Model in Loose Soil

Reiya Takemura, Genya Ishigami

研究成果: Conference contribution

抄録

This paper presents a framework for trajectory planning that explicitly considers robotic traversability based on a quasi-dynamic vehicle model of a mobile robot in loose soil. The quasi-dynamic model estimates the slip effect due to wheel-terrain interaction forces regardless of solving complicated multibody dynamics. Therefore, our proposed model is computationally efficient for quantifying how the robot safely traverses each trajectory segment generated by a planning algorithm. The trajectory planning in our framework exploits a sampling-based incremental search algorithm, i.e., Closed-Loop Rapidly-Exploring Random Trees (CL-RRT). In the tree extension process of the CL-RRT, the traversability assessment based on the quasi-dynamic vehicle model excludes the trajectory segment associated with a hazardous wheel slip ratio. As a result, a trajectory generated from the proposed framework is safely traversable for the robot even in high slip terrain. Simulation results show that the proposed vehicle model can run 57K times faster than the dynamic model and predict the robot motion 3 times more accurately than the kinematic model. Multiple trials of the trajectory planning simulation show that our proposed framework incorporated with the quasi-dynamic model reduces a wheel slip ratio by about 40 % as compared with the kinematic model.

本文言語English
ホスト出版物のタイトルIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ページ8411-8417
ページ数7
ISBN(電子版)9781665417143
DOI
出版ステータスPublished - 2021
イベント2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021 - Prague, Czech Republic
継続期間: 2021 9月 272021 10月 1

出版物シリーズ

名前IEEE International Conference on Intelligent Robots and Systems
ISSN(印刷版)2153-0858
ISSN(電子版)2153-0866

Conference

Conference2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
国/地域Czech Republic
CityPrague
Period21/9/2721/10/1

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ソフトウェア
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ サイエンスの応用

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