Departmental Papers (ESE)

Document Type

Conference Paper

Date of this Version

December 2004

Comments

Copyright 2004 IEEE. Reprinted from Proceedings of the 2004 IEEE Conference on Robotics, Automation and Mechatronics, Volume 2, pages 679-686.

This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

NOTE: At the time of publication, author Daniel Koditschek was affiliated with the University of Michigan. Currently (July 2005), he is a faculty member in the Department of Electrical and Systems Engineering at the University of Pennsylvania.

Abstract

This paper introduces a framework for representing, generating, and then tuning gaits of legged robots. We introduce a convenient parametrization of gait generators as dynamical systems possessing designer specified stable limit cycles over an appropriate torus. This parametrization affords a continuous selection of operation within a coordination design plane, inspired by biology, spanned by axes that determine the mix of "feedforward/feedback" and "centralized/decentralized" control. Tuning the gait generator parameters through repeated physical experiments with our robot hexapod, RHex, determines the appropriate operating point - the mix of feedback and degree of control decentralization - to achieve significantly increased performance relative to the centralized feedforward operating point that has governed its previous behavior. The present preliminary experiments with these new gaits suggest that they may permit for the first time locomotion over extremely rough terrain that is almost as reliable, rapid, and energy efficient as the very fastest or most efficient outcomes centralized feedforward gaits can achieve on level ground.

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Date Posted: 18 July 2005