Compliance while resisting: A shear-thickening fluid controller for physical human-robot interaction

顺从(心理学) 机器人 增稠 控制器(灌溉) 人机交互 剪切(地质) 工程类 计算机科学 控制理论(社会学) 结构工程 控制工程 材料科学 心理学 控制(管理) 人工智能 社会心理学 复合材料 农学 制浆造纸工业 生物
作者
L.Y Chen,Lipeng Chen,Xiangchi Chen,Haojian Lu,Y. Zheng,Jun Wu,Yue Wang,Zhengyou Zhang,Rong Xiong
出处
期刊:The International Journal of Robotics Research [SAGE Publishing]
被引量:1
标识
DOI:10.1177/02783649241234364
摘要

Physical human-robot interaction (pHRI) is widely needed in many fields, such as industrial manipulation, home services, and medical rehabilitation, and puts higher demands on the safety of robots. Due to the uncertainty of the working environment, the pHRI may receive unexpected impact interference, which affects the safety and smoothness of the task execution. The commonly used linear admittance control (L-AC) can cope well with high-frequency small-amplitude noise, but for medium-frequency high-intensity impact, the effect is not as good. Inspired by the solid-liquid phase change nature of shear-thickening fluid, we propose a shear-thickening fluid control (SFC) that can achieve both an easy human-robot collaboration and resistance to impact interference. The SFC’s stability, passivity, and phase trajectory are analyzed in detail, the frequency and time domain properties are quantified, and parameter constraints in discrete control and coupled stability conditions are provided. We conducted simulations to compare the frequency and time domain characteristics of L-AC, nonlinear admittance controller (N-AC), and SFC and validated their dynamic properties. In real-world experiments, we compared the performance of L-AC, N-AC, and SFC in both fixed and mobile manipulators. L-AC exhibits weak resistance to impact. N-AC can resist moderate impacts but not high-intensity ones and may exhibit self-excited oscillations. In contrast, SFC demonstrated superior impact resistance and maintained stable collaboration, enhancing comfort in cooperative water delivery tasks. Additionally, a case study was conducted in a factory setting, further affirming the SFC’s capability in facilitating human-robot collaborative manipulation and underscoring its potential in industrial applications.
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