A Distributed Strategy for Gait Adaptation in Modular Robots

Publication: Research - peer-reviewConference article – Annual report year: 2010

Without internal affiliation

  • Author: Christensen, David Johan

    University of Southern Denmark

  • Author: Schultz, Ulrik Pagh

    University of Southern Denmark

  • Author: Stoy, Kasper

    University of Southern Denmark

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In this paper we study online gait opti- mization for modular robots. The learning strategy we apply is distributed, independent on robot mor- phology, and easy to implement. First we demonstrate how the strategy allows an ATRON robot to adapt to faults and changes in its morphology and we study the strategy’s scalability. Second we extend the strategy to learn the parameters of gait-tables for ATRON and M-TRAN robots.We conclude that the presented strategy is effective for online learning of gaits for most types of modular robots and that learning can effectively be distributed by having independent pro- cesses learning in parallel.
Original languageEnglish
JournalI E E E International Conference on Robotics and Automation. Proceedings
Publication date2010
Pages2765-2770
ISSN1050-4729
DOIs
StatePublished

Conference

Conference2010 IEEE International Conference on Robotics and Automation
CountryUnited States
CityAnchorage, AK
Period03/05/1008/05/10
Internet addresshttp://icra2010.grasp.upenn.edu/
CitationsWeb of Science® Times Cited: No match on DOI
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