Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICSMC.2007.4413595
Title: Autonomous bipedal walking pace supervision under perturbations
Authors: Yang, L.
Chew, C.-M. 
Poo, A.-N. 
Issue Date: 2007
Source: Yang, L., Chew, C.-M., Poo, A.-N. (2007). Autonomous bipedal walking pace supervision under perturbations. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics : 765-770. ScholarBank@NUS Repository. https://doi.org/10.1109/ICSMC.2007.4413595
Abstract: This paper presented a method of bipedal walking pace supervision by the adjustment of stride-frequency and step-length simultaneously. A reinforcement learning algorithm is designed to learn the walking stride-frequency; A transition plan aims to adjust the step-length or update motion phases according to the dynamic feedback; A momentum based estimation gives another layer of stride-frequency adjustment when the learning agent has not gained enough experiences. Simulation experiments showed this learning based motion supervision is effective for maintaining stable walking under perturbations with a balanced performance of energy consumption and robustness. ©2007 IEEE.
Source Title: Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
URI: http://scholarbank.nus.edu.sg/handle/10635/73217
ISBN: 1424409918
ISSN: 1062922X
DOI: 10.1109/ICSMC.2007.4413595
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