Please use this identifier to cite or link to this item: https://doi.org/10.1017/S0263574703005253
Title: Frontal plane algorithms for dynamic bipedal walking
Authors: Chew, C.-M. 
Pratt, G.A.
Keywords: Bipedal walking
Control law
Frontal plane algorithms
Stance-ankle joint roll
Issue Date: Jan-2004
Citation: Chew, C.-M., Pratt, G.A. (2004-01). Frontal plane algorithms for dynamic bipedal walking. Robotica 22 (1) : 29-39. ScholarBank@NUS Repository. https://doi.org/10.1017/S0263574703005253
Abstract: This paper presents two frontal plane algorithms for 3D dynamic bipedal walking. One of which is based on the notion of symmetry and the other uses reinforcement learning algorithm to learn the lateral foot placement. The algorithms are combined with a sagittal plane algorithm and successfully applied to a simulated 3D bipedal robot to achieve level ground walking. The simulation results showed that the choice of the local control law for the stance-ankle roll joint could significantly affect the performance of the frontal plane algorithms.
Source Title: Robotica
URI: http://scholarbank.nus.edu.sg/handle/10635/60382
ISSN: 02635747
DOI: 10.1017/S0263574703005253
Appears in Collections:Staff Publications

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