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Prof. Daniel E. Koditschek

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Gait Generation and Optimization for Legged Robots

IEEE Conference of Robotics and Automation, 2003

J. Weingarten*, M. Buehler†, R. Groff*, D. E. Koditschek*

*: Department of Electrical Engineering and Computer Science, The University of Michigan
†: Center for Intelligent Machines, Ambulatory Robotics Laboratory, McGill University

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      This paper presents a general framework for representing and generating gaits for 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°).
BibTeX Entry
  title={{Gait generation and optimization for legged robots}},
  author={Weingarten, J.D. and Buehler, M. and Groff, R.E. and Koditschek, D.E.},
  booktitle={The IEEE International Conference on Robotics and Automation},
  year = {2002}

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