Please use this identifier to cite or link to this item:
|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|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 13, 2019
checked on Dec 15, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.