VibroBot: A Lightweight and Wirelessly Programmable Vibration Bot for Haptic Guidance

IF 4.6 2区 计算机科学 Q2 ROBOTICS
Xiaosa Li;Runze Zhao;Xinyue Chai;Zimo Wang;Qianqian Tong;Wenbo Ding
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引用次数: 0

Abstract

Cutaneous haptics is helpful to tame the human-machine mismatch by interactive tactile feedback and perform precise manipulations for virtual immersive interactions. However, wearable tactile gloves cover the palm and fingers greatly, thus reducing the tactile information from interactive objects and causing the inconsistency between virtual and practical operations. In this work, we design a lightweight finger-worn vibration bot, named VibroBot, to provide the individual vibrotactile feedback to each finger without compromising the hand dexterity. Each VibroBot, weighing only 2.9 grams, integrates components of the power, a wireless chip and a coil actuator, to receive programmable waveform signals and perform the real-time vibration feedback wirelessly on finger. Our design features six rapidly distinguishable vibration modes with the 96.4% recognition rate in 2.0 s, each guiding one of three finger joints for flexing or extending to a specified angular range. When worn on all five fingers, VibroBots can collaboratively guide the user with multi-dimension semantics, to adjust five fingers for target hand gestures at the same time. In virtual gesture training experiments, VibroBots were used to correct users' muscle memory bias for common gestures, and reduced the average gesture error from about 30 $^\circ$ to less than 15 $^\circ$ . Haptic guidance by VibroBots shows its potential in various Tactile Internet scenarios that require a large number of pretrained hand operations, such as robotic teleoperation and virtual surgical training.
VibroBot:用于触觉引导的轻量级无线可编程振动机器人
皮肤触觉技术有助于通过交互式触觉反馈解决人机失配问题,并在虚拟沉浸式交互中实现精确操作。然而,可穿戴的触觉手套会极大地覆盖手掌和手指,从而减少来自交互对象的触觉信息,造成虚拟操作与实际操作的不一致。在这项工作中,我们设计了一种名为 VibroBot 的轻型指戴式振动机器人,在不影响手部灵活性的情况下为每个手指提供单独的振动触觉反馈。每个 VibroBot 仅重 2.9 克,集成了电源、无线芯片和线圈致动器等组件,可接收可编程波形信号,并通过无线方式对手指进行实时振动反馈。我们的设计具有六种可快速区分的振动模式,在 2.0 秒内的识别率高达 96.4%,每种模式都能引导手指的三个关节之一弯曲或伸展到指定的角度范围。当五根手指都戴上振动机器人时,它可以通过多维语义协同引导用户同时调整五根手指做出目标手势。在虚拟手势训练实验中,VibroBots 用于纠正用户对常用手势的肌肉记忆偏差,并将平均手势误差从约 30 美元/圈减少到 15 美元/圈以下。VibroBots 的触觉引导显示了它在各种需要大量预先训练的手部操作的触觉互联网应用场景中的潜力,例如机器人远程操作和虚拟手术训练。
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
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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