基于导纳的仿生认知PID控制优化动力辅助物体操作中人机交互

S. Rahman
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引用次数: 1

摘要

提出了一种新的PID控制方法,以优化动力辅助机器人系统(PARS)的人机交互(HRI)。PID控制以导纳控制的形式发展起来。为了从生物角度出发,使控制与人类认知相适应,提出了一种将体重感知纳入系统动力学和控制的新方法。然后,提出了一种综合评价和优化方案,以确定最佳的HRI和协同操作性能。开发了一个1-DOF试验台,在中试研究中实验验证了所提出的控制方法。在实验过程中,实验对象用该系统举起物体,并对HRI和系统特性进行了调查和分析。结果表明,通过在动力学和控制中加入权重感知,所提出的符合人类认知的PID控制可以有效地优化HRI和协同操作性能。研究结果可用于为pars设计以人为中心的控制方法,以帮助人类在工业和家庭中操纵重物,从而提供最佳的HRI和操作性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Admittance-Based Bio-Inspired Cognitive PID Control to Optimize Human-Robot Interaction in Power-Assisted Object Manipulation
A novel approach to PID control for optimizing human-robot interaction (HRI) in manipulating objects with a power assist robotic system (PARS) was presented. The PID control was developed in the form of the admittance control. To take bio-inspiration and fit the control with human cognition, a novel method of inclusion of weight perception in the dynamics and control of the system was proposed. Then, a comprehensive evaluation and optimization scheme was proposed to determine the optimum HRI and co-manipulation performance. A 1-DOF testbed PARS was developed to experimentally verify the proposed control in a pilot study. During the experiments, human subjects lifted objects with the system and the HRI and system characteristics were investigated and analyzed. The results showed that the proposed PID control aligned with human cognition through inclusion of weight perception in the dynamics and control was effective to optimize the HRI and co-manipulation performance. The results can be used to design human-centered control methods for PARSs to assist humans manipulating heavy objects in industries and at homes that can provide optimum HRI and manipulation performance.
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