Enhancing free-space transparency with discrete energy-based compensation in physical human–robot interaction

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems Pub Date : 2025-02-11 DOI:10.1016/j.robot.2025.104940

Seung Ho Lee, Ji Min Baek, Hyungpil Moon, Hyouk Ryeol Choi, Ja Choon Koo

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Abstract

In physical human–robot interaction (pHRi), free-space transparency reflects how accurately a robot interprets and follows human motion intentions. This paper presents a novel discrete energy-based compensator designed to enhance transparency by leveraging an admittance controller that requires real-time input compensation. Transparency, defined as the work performed by interaction forces per unit distance, is improved by analyzing human dynamics to minimize interaction forces linked to transparency. The proposed compensator incorporates time delay control to compute necessary real-time compensation based on interactions between human and robot dynamics represented by admittance parameters. The method was validated through simulations and experiments on a physical robot system, demonstrating its effectiveness in enhancing transparency while addressing practical limitations. This study emphasizes the importance of dynamic analysis in pHRi and proposes a cost-effective approach to compensate for both interaction and robot dynamics.

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物理人机交互中离散能量补偿增强自由空间透明度

在物理人机交互（pHRi）中，自由空间透明度反映了机器人如何准确地解释和遵循人类的运动意图。本文提出了一种新的离散能量补偿器，通过利用需要实时输入补偿的导纳控制器来提高透明度。透明度，定义为每单位距离的相互作用力所完成的功，通过分析人类动力学来最小化与透明度相关的相互作用力来改进。该补偿器结合时延控制，根据以导纳参数表示的人与机器人动力学之间的相互作用计算必要的实时补偿。该方法通过物理机器人系统的仿真和实验进行了验证，证明了其在提高透明度同时解决实际限制方面的有效性。本研究强调了动态分析在pHRi中的重要性，并提出了一种具有成本效益的方法来补偿相互作用和机器人动力学。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Robotics and Autonomous Systems 工程技术-机器人学

CiteScore

9.00

自引率

7.00%

发文量

164

审稿时长

4.5 months

期刊介绍： Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.