Dynamic simulation-based action planner for a reconfigurable hybrid leg-wheel planetary exploration rover

Eric Rohmer, Giulio Reina, Kazuya Yoshida

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

In this paper, an action planning algorithm is presented for a reconfigurable hybrid leg-wheel mobile robot. Hybrid leg-wheel robots have recently receiving growing interest from the space community to explore planets, as they offer a solution to improve speed and mobility on uneven terrain. One critical issue connected with them is the study of an appropriate strategy to define when to use one over the other locomotion mode, depending on the soil properties and topology. Although this step is crucial to reach the full hybrid mechanism's potential, little attention has been devoted to this topic. Given an elevation map of the environment, we developed an action planner that selects the appropriate locomotion mode along an optimal path toward a point of scientific interest. This tool is helpful for the space mission team to decide the next move of the robot during the exploration. First, a candidate path is generated based on topology and specifications' criteria functions. Then, switching actions are defined along this path based on the robot's performance in each motion mode. Finally, the path is rated based on the energy profile evaluated using a dynamic simulator. The proposed approach is applied to a concept prototype of a reconfigurable hybrid wheel-leg robot for planetary exploration through extensive simulations and real experiments.

Original languageEnglish
Pages (from-to)1219-1238
Number of pages20
JournalAdvanced Robotics
Volume24
Issue number8-9
DOIs
Publication statusPublished - 2010 May 1

Keywords

  • Action planning
  • Hybrid leg-wheel mechanism
  • Lanetary exploration
  • Reconfigurable robot

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Science Applications

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