Wheel Design Methodology for a Lunar Exploration Rover in Order to Improve Trafficability Considering Operation Environment

  • Kun Jung Kim
  • , Byeong Seop Sim
  • , Seong Hwan Kim
  • , Kee Ho Yu

Research output: Contribution to conferenceConference paperpeer-review

Abstract

For achieving a successful mission in lunar exploration, not only traversability of exploration rover should be predicted but also operation environment should be considered under the limited power condition. Therefore, an optimal design of rover wheel for minimizing power consumption and maximizing tractive performance is required by conducting conceptual design stage. This paper describes settlement of requirements at system level and modeling of operation environment such as power acquisition and terrain characteristics in the lunar simulant. Using the wheel-terrain interaction model, a wheel design methodology was proposed to obtain an optimal wheel dimension, which meet the limited power condition along with maximal trafficability according to the each landing site. In addition, the results from the above approach have been validated with the experimental results using a single wheel test bed on the lunar simulant.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Robotics and Automation, ICRA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages904-909
Number of pages6
ISBN (Electronic)9781538630815
DOIs
StatePublished - 2018.09.10
Event2018 IEEE International Conference on Robotics and Automation, ICRA 2018 - Brisbane, Australia
Duration: 2018.05.212018.05.25

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2018 IEEE International Conference on Robotics and Automation, ICRA 2018
Country/TerritoryAustralia
CityBrisbane
Period18.05.2118.05.25

Quacquarelli Symonds(QS) Subject Topics

  • Computer Science & Information Systems
  • Engineering - Electrical & Electronic
  • Engineering - Petroleum
  • Data Science

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