A uniform biped gait generator with offline optimization and online adjustable parameters

Authors:
Lin Yang;Chee-Meng Chew;Teresa Zielinska;Aun-Neow Poo
Affiliations:
Control and Mechatronics Lab, Department of Mechanical Engineering, The National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore;Control and Mechatronics Lab, Department of Mechanical Engineering, The National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore;Warsaw University of Technology, Institute for Aircraft Engineering and Applied Mechanics, 00-665 Warsaw, Poland;Control and Mechatronics Lab, Department of Mechanical Engineering, The National University of Singapore, 10 Kent Ridge Crescent, Singapore 119260, Singapore
Venue:
Robotica
Year:
2007

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Abstract

This paper presents the Genetic Algorithm Optimized Fourier Series Formulation (GAOFSF) method for stable gait generation in bipedal locomotion. It uses a Truncated Fourier Series (TFS) formulation with its coefficients determined and optimized by Genetic Algorithm. The GAOFSF method can generate human-like stable gaits for walking on flat terrains as well as on slopes in a uniform way. Through the adjustment of only a single or two parameters, the step length and stride-frequency can easily be adjusted online, and slopes of different gradients are accommodated. Dynamic simulations show the robustness of the GAOFSF, with stable gaits achieved even if the step length and stride frequency are adjusted by significant amounts. With its ease of adjustments to accommodate different gait requirements, the approach lends itself readily for control of walking on a rough terrain and in the presence of external perturbations.