An online impedance adaptation controller for decoding skill intelligence

Xiaofeng Xiong , Cheng Fang
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引用次数: 1

Abstract

Variable Impedance control allows robots and humans to safely and efficiently interact with unknown external environments. This tutorial introduces online impedance adaptation control (OIAC) for variable compliant joint motions in a range of control tasks: rapid (<1s) movement control (i.e., whipping to hit), arm and finger impedance quantification, multifunctional exoskeleton control, and robot-inspired human arm control hypothesis. The OIAC has been introduced as a feedback control, which can be integrated into a feedforward control, e.g., learned by data-driven methods. This integration facilitates the understanding of human and robot arm control, closing a research loop between biomechanics and robotics. It shows not only a research way from biomechanics to robotics, but also another reserved one. This tutorial aims at presenting research examples and Python codes for advancing the understanding of variable impedance adaptation in human and robot motor control. It contributes to the state-of-the-art by providing an online impedance adaptation controller for wearable robots (i.e., exoskeletons) which can be used in robotic and biomechanical applications.

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一种用于解码技能智能的阻抗在线自适应控制器
可变阻抗控制使机器人和人类能够安全有效地与未知的外部环境进行交互。本教程介绍了一系列控制任务中用于可变顺应性关节运动的在线阻抗自适应控制(OIAC):快速(<;1s)运动控制(即鞭打到击打)、手臂和手指阻抗量化、多功能外骨骼控制以及机器人启发的人类手臂控制假设。OIAC已被引入作为反馈控制,其可以被集成到前馈控制中,例如,通过数据驱动方法学习。这种集成促进了对人类和机器人手臂控制的理解,闭合了生物力学和机器人之间的研究循环。它不仅展示了一条从生物力学到机器人学的研究之路,也展示了另一条保留之路。本教程旨在介绍研究示例和Python代码,以促进对人类和机器人电机控制中可变阻抗自适应的理解。它为可穿戴机器人(即外骨骼)提供了一种在线阻抗自适应控制器,可用于机器人和生物力学应用,从而为最先进技术做出了贡献。
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