Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-540-73424-6_22
Title: Autonomous stride-frequency and step-length adjustment for bipedal walking control
Authors: Yang, L.
Chew, C.-M. 
Poo, A.-N. 
Zielinska, T.
Issue Date: 2007
Source: Yang, L.,Chew, C.-M.,Poo, A.-N.,Zielinska, T. (2007). Autonomous stride-frequency and step-length adjustment for bipedal walking control. Studies in Computational Intelligence 76 : 189-198. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-540-73424-6_22
Abstract: This work focuses on the stride-frequency and step-length autonomous adjustment in response to the environment perturbations. Reinforcement learning is assigned to supervise the stride-frequency. A simple momentum estimation further promised the adjustment. In the learning agent, a sorted action-choose table instructed the learning to find out the proper action in a straightforward way. Incorporating the step-length real-time adjustment mode, the biped is able to smoothly transit motions and walk adaptively to the environment. Dynamic simulation results showed that the supervision is effective. © 2007 Springer-Verlag Berlin Heidelberg.
Source Title: Studies in Computational Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/59613
ISBN: 3540734236
ISSN: 1860949X
DOI: 10.1007/978-3-540-73424-6_22
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