Sinnet, Ryan W. and Ames, Aaron D. (2009) 2D bipedal walking with knees and feet: A hybrid control approach. In: Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference. IEEE , Piscataway, NJ, pp. 3200-3207. ISBN 978-1-4244-3872-3. https://resolver.caltech.edu/CaltechAUTHORS:20190226-091428821
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Abstract
In this paper, we consider an anthropomorphically-inspired hybrid model of a bipedal robot with locking knees and feet in order to develop a control law that results in human-like walking. The presence of feet results in periods of full actuation and periods of underactuation during the course of a step. Properties of each of these phases of walking are utilized in order to achieve a stable walking gait. In particular, we will show that using controlled symmetries in the fully-actuated domains coupled with ¿partial¿ controlled symmetries and local ankle control laws in the underactuated domains yields stable walking; this result is possible due to the amount of time which the biped spends in the fully-actuated domains. The paper concludes with simulation results along with a comparison of these results to human walking data.
Item Type: | Book Section | ||||||
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Additional Information: | © 2009 IEEE. | ||||||
DOI: | 10.1109/CDC.2009.5400503 | ||||||
Record Number: | CaltechAUTHORS:20190226-091428821 | ||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20190226-091428821 | ||||||
Official Citation: | R. W. Sinnet and A. D. Ames, "2D bipedal walking with knees and feet: A hybrid control approach," Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, 2009, pp. 3200-3207. doi: 10.1109/CDC.2009.5400503 | ||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||
ID Code: | 93249 | ||||||
Collection: | CaltechAUTHORS | ||||||
Deposited By: | Tony Diaz | ||||||
Deposited On: | 26 Feb 2019 17:18 | ||||||
Last Modified: | 16 Nov 2021 16:56 |
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