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Humanoid adaptive locomotion control through a bioinspired CPG-based controller

Published online by Cambridge University Press:  22 June 2021

Chenpeng Yao
Affiliation:
Department of Control Science and Engineering, Tongji University, Shanghai201804, China Tongji artificial intelligence (Suzhou) Research Institute, Suzhou215000, China
Chengju Liu*
Affiliation:
Department of Control Science and Engineering, Tongji University, Shanghai201804, China Tongji artificial intelligence (Suzhou) Research Institute, Suzhou215000, China
Li Xia
Affiliation:
Department of Control Science and Engineering, Tongji University, Shanghai201804, China
Ming Liu
Affiliation:
Department of Electronic and Computer Engineering, the Hong Kong University of Science and Technology, Hong Kong999077, China
Qijun Chen
Affiliation:
Department of Control Science and Engineering, Tongji University, Shanghai201804, China
*
*Corresponding author. Email: liuchengju@tongji.edu.cn

Abstract

To achieve adaptive gait planning of humanoid robots, a hierarchical central pattern generator (H-CPG) model with a basic rhythmic signal generation layer and a pattern formation layer is proposed to modulate the center of mass (CoM) and the online foot trajectory. The entrainment property of the CPG is exploited for adaptive walking in the absence of a priori knowledge of walking conditions, and the sensory feedback is applied to modulate the generated trajectories online to improve walking adaptability and stability. The developed control strategy is verified using a humanoid robot on sloped terrain and shows good performance.

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© The Author(s), 2021. Published by Cambridge University Press

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Yao et al. supplementary material

Yao et al. supplementary material

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