触觉技术
人机交互
摩擦电效应
计算机科学
虚拟现实
接口(物质)
增强现实
有线手套
触觉传感器
人工智能
模拟
材料科学
机器人
最大气泡压力法
气泡
复合材料
并行计算
作者
Minglu Zhu,Zhongda Sun,Zixuan Zhang,Qiongfeng Shi,Tianyiyi He,Huicong Liu,Tao Chen,Chengkuo Lee
出处
期刊:Science Advances
[American Association for the Advancement of Science (AAAS)]
日期:2020-05-08
卷期号:6 (19)
被引量:531
标识
DOI:10.1126/sciadv.aaz8693
摘要
Human-machine interfaces (HMIs) experience increasing requirements for intuitive and effective manipulation. Current commercialized solutions of glove-based HMI are limited by either detectable motions or the huge cost on fabrication, energy, and computing power. We propose the haptic-feedback smart glove with triboelectric-based finger bending sensors, palm sliding sensor, and piezoelectric mechanical stimulators. The detection of multidirectional bending and sliding events is demonstrated in virtual space using the self-generated triboelectric signals for various degrees of freedom on human hand. We also perform haptic mechanical stimulation via piezoelectric chips to realize the augmented HMI. The smart glove achieves object recognition using machine learning technique, with an accuracy of 96%. Through the integrated demonstration of multidimensional manipulation, haptic feedback, and AI-based object recognition, our glove reveals its potential as a promising solution for low-cost and advanced human-machine interaction, which can benefit diversified areas, including entertainment, home healthcare, sports training, and medical industry.
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