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一种基于振动触觉反馈的肌控机器人手抓握力调节控制架构:初步结果

A Control Architecture for Grasp Strength Regulation in Myocontrolled Robotic Hands Using Vibrotactile Feedback: Preliminary Results.

作者信息

Meattini Roberto, Biagiotti Luigi, Palli Gianluca, De Gregorio Daniele, Melchiorri Claudio

出版信息

IEEE Int Conf Rehabil Robot. 2019 Jun;2019:1272-1277. doi: 10.1109/ICORR.2019.8779476.

Abstract

Nowadays, electric-powered hand prostheses do not provide adequate sensory instrumentation and artificial feedback to allow users voluntarily and finely modulate the grasp strength applied to the objects. In this work, the design of a control architecture for a myocontrol-based regulation of the grasp strength for a robotic hand equipped with contact force sensors is presented. The goal of the study was to provide the user with the capability of modulating the grasping force according to target required levels by exploiting a vibrotactile feedback. In particular, the whole human-robot control system is concerned (i.e. myocontrol, robotic hand controller, vibrotactile feedback.) In order to evaluate the intuitiveness and force tracking performance provided by the proposed control architecture, an experiment was carried out involving four naïve able-bodied subjects in a grasping strength regulation task with a myocontrolled robotic hand (the University of Bologna Hand), requiring for grasping different objects with specific target force levels. The reported results show that the control architecture successfully allowed all subjects to achieve all grasping strength levels exploiting the vibrotactile feedback information. This preliminary demonstrates that, potentially, the proposed control interface can be profitably exploited in upper-limb prosthetic applications, as well as for non-rehabilitation uses, e.g. in ultra-light teleoperation for grasping devices.

摘要

如今,电动假手无法提供足够的传感装置和人工反馈,以让用户自主且精细地调节施加在物体上的抓握力。在这项工作中,提出了一种基于肌电控制的抓握力调节控制架构的设计,该架构用于配备接触力传感器的机器人手。本研究的目标是通过利用振动触觉反馈,为用户提供根据目标所需水平调节抓握力的能力。特别地,整个机器人控制系统都在考虑范围内(即肌电控制、机器人手控制器、振动触觉反馈)。为了评估所提出的控制架构的直观性和力跟踪性能,进行了一项实验,让四名没有经验的身体健全的受试者参与使用肌电控制的机器人手(博洛尼亚大学手)进行抓握力调节任务,要求以特定目标力水平抓握不同物体。报告结果表明,该控制架构成功地让所有受试者利用振动触觉反馈信息达到了所有抓握力水平。这初步证明,所提出的控制界面在上肢假肢应用以及非康复用途(例如用于抓握设备的超轻型遥操作)中可能会得到有益的应用。

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