Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/73216
Title: Autonomous bipedal walking gait adjustment under perturbations
Authors: Yang, L.
Chew, C.M. 
Poo, A.N. 
Keywords: Q learning CMAC network real-time walking stride-frequency walking step-length
Issue Date: 2007
Source: Yang, L.,Chew, C.M.,Poo, A.N. (2007). Autonomous bipedal walking gait adjustment under perturbations. Advances in Climbing and Walking Robots - Proceedings of 10th International Conference, CLAWAR 2007 : 309-318. ScholarBank@NUS Repository.
Abstract: This work focuses on the walking stride-frequency autonomous adjustment in response to the environment perturbations. Reinforcement learning is assigned to supervise the stride-frequency. A simple momentum estimation further assisted 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 real-time steplength adjustment mode, the presented gait adjustment is able to achieve different pace walking adaptive to the environment. Dynamic simulation result shows the supervision is effective. © 2007 World Scientific Publishing Co. Pte. Ltd.
Source Title: Advances in Climbing and Walking Robots - Proceedings of 10th International Conference, CLAWAR 2007
URI: http://scholarbank.nus.edu.sg/handle/10635/73216
ISBN: 9812708154
Appears in Collections:Staff Publications

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