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|Title:||Autonomous stride-frequency and step-length adjustment for bipedal walking control||Authors:||Yang, L.
|Issue Date:||2007||Citation:||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|
|Appears in Collections:||Staff Publications|
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