Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-540-73424-6_22
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dc.titleAutonomous stride-frequency and step-length adjustment for bipedal walking control
dc.contributor.authorYang, L.
dc.contributor.authorChew, C.-M.
dc.contributor.authorPoo, A.-N.
dc.contributor.authorZielinska, T.
dc.date.accessioned2014-06-17T06:13:32Z
dc.date.available2014-06-17T06:13:32Z
dc.date.issued2007
dc.identifier.citationYang, 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. <a href="https://doi.org/10.1007/978-3-540-73424-6_22" target="_blank">https://doi.org/10.1007/978-3-540-73424-6_22</a>
dc.identifier.isbn3540734236
dc.identifier.issn1860949X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/59613
dc.description.abstractThis 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-540-73424-6_22
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.doi10.1007/978-3-540-73424-6_22
dc.description.sourcetitleStudies in Computational Intelligence
dc.description.volume76
dc.description.page189-198
dc.identifier.isiutNOT_IN_WOS
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