Statistical mobility prediction for planetary surface exploration rovers in uncertain terrain

Genya Ishigami, Gaurav Kewlani, Karl Iagnemma

研究成果: Conference contribution

19 被引用数 (Scopus)

抄録

Planetary surface exploration rovers must accurately and efficiently predict their mobility on natural, rough terrain. Most approaches to mobility prediction assume precise a priori knowledge of terrain physical parameters, however in practical scenarios knowledge of terrain parameters contains significant uncertainty. In this paper, a statistical method for mobility prediction that incorporates terrain uncertainty is presented. The proposed method consists of two techniques: a wheeled vehicle model for calculating vehicle dynamic motion and wheel-terrain interaction forces, and a stochastic response surface method (SRSM) for modeling of uncertainty. The proposed method generates a predicted motion path of the rover with confidence ellipses indicating the probable rover position due to uncertainty in terrain physical parameters. Rover orientations and wheel slippage are also predicted. The computational efficiency of SRSM as compared to conventional Monte Carlo methods is shown via numerical simulations. Experimental results of rover travel over sloped terrain in two different uncertain terrains are presented that confirms the utility of the proposed mobility prediction method.

本文言語English
ホスト出版物のタイトル2010 IEEE International Conference on Robotics and Automation, ICRA 2010
ページ588-593
ページ数6
DOI
出版ステータスPublished - 2010
外部発表はい
イベント2010 IEEE International Conference on Robotics and Automation, ICRA 2010 - Anchorage, AK, United States
継続期間: 2010 5月 32010 5月 7

出版物シリーズ

名前Proceedings - IEEE International Conference on Robotics and Automation
ISSN(印刷版)1050-4729

Other

Other2010 IEEE International Conference on Robotics and Automation, ICRA 2010
国/地域United States
CityAnchorage, AK
Period10/5/310/5/7

ASJC Scopus subject areas

  • ソフトウェア
  • 制御およびシステム工学
  • 人工知能
  • 電子工学および電気工学

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