Statistical mobility prediction for planetary surface exploration rovers in uncertain terrain

Genya Ishigami, Gaurav Kewlani, Karl Iagnemma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
Pages588-593
Number of pages6
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 IEEE International Conference on Robotics and Automation, ICRA 2010 - Anchorage, AK, United States
Duration: 2010 May 32010 May 7

Other

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

Fingerprint

Wheels
Computational efficiency
Statistical methods
Monte Carlo methods
Uncertainty
Computer simulation

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Ishigami, G., Kewlani, G., & Iagnemma, K. (2010). Statistical mobility prediction for planetary surface exploration rovers in uncertain terrain. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 588-593). [5509300] https://doi.org/10.1109/ROBOT.2010.5509300

Statistical mobility prediction for planetary surface exploration rovers in uncertain terrain. / Ishigami, Genya; Kewlani, Gaurav; Iagnemma, Karl.

Proceedings - IEEE International Conference on Robotics and Automation. 2010. p. 588-593 5509300.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ishigami, G, Kewlani, G & Iagnemma, K 2010, Statistical mobility prediction for planetary surface exploration rovers in uncertain terrain. in Proceedings - IEEE International Conference on Robotics and Automation., 5509300, pp. 588-593, 2010 IEEE International Conference on Robotics and Automation, ICRA 2010, Anchorage, AK, United States, 10/5/3. https://doi.org/10.1109/ROBOT.2010.5509300
Ishigami G, Kewlani G, Iagnemma K. Statistical mobility prediction for planetary surface exploration rovers in uncertain terrain. In Proceedings - IEEE International Conference on Robotics and Automation. 2010. p. 588-593. 5509300 https://doi.org/10.1109/ROBOT.2010.5509300
Ishigami, Genya ; Kewlani, Gaurav ; Iagnemma, Karl. / Statistical mobility prediction for planetary surface exploration rovers in uncertain terrain. Proceedings - IEEE International Conference on Robotics and Automation. 2010. pp. 588-593
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