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基于同步的协作机器人控制

Synchronization-based control for a collaborative robot.

作者信息

Eberle Henry, Nasuto Slawomir J, Hayashi Yoshikatsu

机构信息

Department of Orthopaedics and Musculoskeletal Science, Division of Surgery, University College London, London WC1E 6BT, UK.

Brain Embodiment Lab, Biomedical Engineering, School of Biological Sciences, University of Reading, Reading RG6 6AH, UK.

出版信息

R Soc Open Sci. 2020 Dec 16;7(12):201267. doi: 10.1098/rsos.201267. eCollection 2020 Dec.

Abstract

This article introduces a new control scheme for controlling a robotic manipulator in a collaborative task, allowing it to respond proactively to its partner's movements. Unlike conventional robotic systems, humans can operate in an unstructured, dynamic environment due to their ability to anticipate changes before they occur and react accordingly. Recreating this artificially by using a forward model would lead to the huge computational task of simulating a world full of complex nonlinear dynamics and autonomous human agents. In this study, a controller based on anticipating synchronization, where a 'leader' dynamical system is predicted by a coupled 'follower' with delayed self-feedback, is used to modify a robot's dynamical behaviour to follow that of a series of leaky integrators and harmonic oscillators. This allows the robot (follower) to be coupled with a collaborative partner (leader) to anticipate its movements, without a complete model of its behaviour. This is tested by tasking a simulated Baxter robot with performing a collaborative manual coordination task with an autonomous partner under a range of feedback delay conditions, confirming its ability to anticipate using oscillators instead of a detailed forward model.

摘要

本文介绍了一种用于在协作任务中控制机器人操纵器的新控制方案,使其能够对合作伙伴的动作做出主动响应。与传统机器人系统不同,人类能够在非结构化、动态环境中操作,因为他们有能力在变化发生之前预测变化并做出相应反应。通过使用前向模型来人工重现这一点将导致模拟一个充满复杂非线性动力学和自主人类智能体的世界的巨大计算任务。在本研究中,一种基于预期同步的控制器被用于修改机器人的动力学行为,使其跟随一系列泄漏积分器和谐波振荡器的行为。在这种控制器中,一个“领导者”动态系统由一个带有延迟自反馈的耦合“跟随者”预测。这使得机器人(跟随者)能够与协作伙伴(领导者)耦合,以预测其动作,而无需其行为的完整模型。通过要求一个模拟的Baxter机器人在一系列反馈延迟条件下与一个自主伙伴执行协作手动协调任务来对此进行测试,证实了其使用振荡器而不是详细前向模型进行预测的能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2ff2/7813249/f959bdd95625/rsos201267-g1.jpg

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