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A heuristic gait template planning and dynamic motion control for biped robots

Published online by Cambridge University Press:  15 November 2022

Lianqiang Han
Affiliation:
School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
Xuechao Chen*
Affiliation:
School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
Zhangguo Yu
Affiliation:
School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
Zhifa Gao
Affiliation:
School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
Gao Huang
Affiliation:
Faculty of Information Technology, Beijing University of Technology, Beijing, China
Jintao Zhang
Affiliation:
School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
Kenji Hashimoto
Affiliation:
Department of Mechanical Engineering Informatics, Meiji University/Humanoid Robotics Institute (HRI), Waseda University, Kanagawa, Japan
Qiang Huang
Affiliation:
School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
*
*Corresponding author. E-mail: chenxuechao@bit.edu.cn

Abstract

Biped robots with dynamic motion control have shown strong robustness in complex environments. However, many motion planning methods rely on models, which have difficulty dynamically modifying the walking cycle, height, and other gait parameters to cope with environmental changes. In this study, a heuristic model-free gait template planning method with dynamic motion control is proposed. The gait trajectory can be generated by inputting the desired speed, walking cycle, and support height without a model. Then, the stable walking of the biped robot can be realized by foothold adjustment and whole-body dynamics model control. The gait template can be changed in real time to achieve gait flexibility of the biped robot. Finally, the effectiveness of the method is verified by simulations and experiments of the biped robot BHR-B2. The research presented here helps improve the gait transition ability of biped robots in dynamic locomotion.

Information

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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