Adaptability Control Towards Complex Ground Based on Fuzzy Logic for Humanoid Robots

Chencheng Dong; Zhangguo Yu; Xuechao Chen; Huanzhong Chen; Yan Huang; Qiang Huang

doi:10.1109/TFUZZ.2022.3167458

Adaptability Control Towards Complex Ground Based on Fuzzy Logic for Humanoid Robots

Chencheng Dong
, Zhangguo Yu^*
, Xuechao Chen^*
, Huanzhong Chen
, Yan Huang
, Qiang Huang

^*Corresponding author for this work

School of Mechatronical Engineering

Beijing Institute of Technology
Ministry of Education in China

Research output: Contribution to journal › Article › peer-review

57 Citations (Scopus)

Abstract

Stability control for humanoid robots based on zero moment point (ZMP) control and impedance control are widespread. However, uncertain changes in the center of mass (CoM) height for ZMP control and specific regulation of the variable stiffness of impedance control have been challenging issues in previous studies. In this article, these two problems are solved by implementing fuzzy control-based regulations. First, the fuzzy ZMP controller, which regulates the feedback gains online based on the CoM height change and CoM tracking errors, is proposed. Second, we propose a fuzzy regulation law for variable stiffness, which is applied for uncertain contact situations and inspired by the pattern of human muscle stiffness. With these two methods, the ground adaptability for humanoid robots is enhanced. The proposed method is validated with experiments on a real robot platform, BHR-T.

Original language	English
Pages (from-to)	1574-1584
Number of pages	11
Journal	IEEE Transactions on Fuzzy Systems
Volume	30
Issue number	6
DOIs	https://doi.org/10.1109/TFUZZ.2022.3167458
Publication status	Published - 1 Jun 2022

Keywords

Balance control
foot contact control
fuzzy control
humanoid robot

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10.1109/TFUZZ.2022.3167458

Cite this

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title = "Adaptability Control Towards Complex Ground Based on Fuzzy Logic for Humanoid Robots",

abstract = "Stability control for humanoid robots based on zero moment point (ZMP) control and impedance control are widespread. However, uncertain changes in the center of mass (CoM) height for ZMP control and specific regulation of the variable stiffness of impedance control have been challenging issues in previous studies. In this article, these two problems are solved by implementing fuzzy control-based regulations. First, the fuzzy ZMP controller, which regulates the feedback gains online based on the CoM height change and CoM tracking errors, is proposed. Second, we propose a fuzzy regulation law for variable stiffness, which is applied for uncertain contact situations and inspired by the pattern of human muscle stiffness. With these two methods, the ground adaptability for humanoid robots is enhanced. The proposed method is validated with experiments on a real robot platform, BHR-T.",

keywords = "Balance control, foot contact control, fuzzy control, humanoid robot",

author = "Chencheng Dong and Zhangguo Yu and Xuechao Chen and Huanzhong Chen and Yan Huang and Qiang Huang",

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AU - Dong, Chencheng

AU - Yu, Zhangguo

AU - Chen, Xuechao

AU - Chen, Huanzhong

AU - Huang, Yan

AU - Huang, Qiang

PY - 2022/6/1

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AB - Stability control for humanoid robots based on zero moment point (ZMP) control and impedance control are widespread. However, uncertain changes in the center of mass (CoM) height for ZMP control and specific regulation of the variable stiffness of impedance control have been challenging issues in previous studies. In this article, these two problems are solved by implementing fuzzy control-based regulations. First, the fuzzy ZMP controller, which regulates the feedback gains online based on the CoM height change and CoM tracking errors, is proposed. Second, we propose a fuzzy regulation law for variable stiffness, which is applied for uncertain contact situations and inspired by the pattern of human muscle stiffness. With these two methods, the ground adaptability for humanoid robots is enhanced. The proposed method is validated with experiments on a real robot platform, BHR-T.

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Adaptability Control Towards Complex Ground Based on Fuzzy Logic for Humanoid Robots

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Keywords

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