Departmental Papers (ESE)


This paper presents a general framework for representing and generating gaitsfor legged robots. We introduce a convenient parametrization of gait generators as dynamical systems possessing specified stable limit cycles over an appropriate torus. Inspired by biology, this parametrization affords a continuous selection of operation within a coordination design plane spanned by axes that determine the mix of ”feedforward/feedback” and centralized/decentralized” control. Applying optimization to the parameterized gait generation system allowed RHex, our robotic hexapod, to learn new gaits demonstrating significant performance increases. For example, RHex can now run at 2.4m/s (up from 0.8m/s), run with a specific resistance of 0.6 (down from 2.0), climb 45 inclines (up from 25), and traverse 35 inclines (up from 15).

Document Type

Conference Paper

Subject Area

GRASP, Kodlab

Date of this Version


Publication Source

IEEE International Conference on Robotics and Automation

Copyright/Permission Statement

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Date Posted: 17 December 2020

This document has been peer reviewed.