Action module planning and its application to an experimental climbing robot

David M. Bevly, Shane Farritor, Steven Dubowsky

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


This paper presents the application of an action module planning method to an experimental climbing robot named LIBRA. The method searches for a sequence of physically realizable actions, called action modules, to produce a plan for a given task. The search is performed with a hierarchical selection process that uses task and configuration filters to reduce the action module inventory to a reasonable search space. Then, a genetic algorithm search finds a sequence of actions that allows the robot to complete the task without violating any physical constraints. The results for the LIBRA climbing robot show the method is able to produce effective plans.

Original languageEnglish (US)
Pages (from-to)4009-4014
Number of pages6
JournalProceedings-IEEE International Conference on Robotics and Automation
StatePublished - Apr 2000

ASJC Scopus subject areas

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


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