Design and experimental study of a passive power-source-free stiffness-self-adjustable mechanism

Yuwang LIU, Dongqi WANG, Shangkui YANG, Jinguo LIU, Guangbo HAO

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Front. Mech. Eng. ›› 2021, Vol. 16 ›› Issue (1) : 32-45. DOI: 10.1007/s11465-020-0604-4
RESEARCH ARTICLE

Design and experimental study of a passive power-source-free stiffness-self-adjustable mechanism

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Abstract

Passive variable stiffness joints have unique advantages over active variable stiffness joints and are currently eliciting increased attention. Existing passive variable stiffness joints rely mainly on sensors and special control algorithms, resulting in a bandwidth-limited response speed of the joint. We propose a new passive power-source-free stiffness-self-adjustable mechanism that can be used as the elbow joint of a robot arm. The new mechanism does not require special stiffness regulating motors or sensors and can realize large-range self-adaptive adjustment of stiffness in a purely mechanical manner. The variable stiffness mechanism can automatically adjust joint stiffness in accordance with the magnitude of the payload, and this adjustment is a successful imitation of the stiffness adjustment characteristics of the human elbow. The response speed is high because sensors and control algorithms are not needed. The variable stiffness principle is explained, and the design of the variable stiffness mechanism is analyzed. A prototype is fabricated, and the associated hardware is set up to validate the analytical stiffness model and design experimentally.

Keywords

variable stiffness mechanism / stiffness self-regulation / bionic robot / modeling

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Yuwang LIU, Dongqi WANG, Shangkui YANG, Jinguo LIU, Guangbo HAO. Design and experimental study of a passive power-source-free stiffness-self-adjustable mechanism. Front. Mech. Eng., 2021, 16(1): 32‒45 https://doi.org/10.1007/s11465-020-0604-4

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Acknowledgements

The authors express their gratitude to the referees for carefully reading the paper and providing constructive comments and detailed suggestions for improvement. The authors are also thankful to postgraduate student Qiang Cheng for his support during the writing of the paper. This study was supported by the National Key R&D Program of China (Grant No. 2018YFB1304600), the National Natural Science Foundation of China (Grant Nos. 51975566 and 61821005), and the CAS Interdisciplinary Innovation Team (Grant No. JCTD-2018-11).

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2021 The Author(s) 2021. This article is published with open access at link.springer.com and journal.hep.com.cn
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