接口
抓住
有线手套
对象(语法)
计算机视觉
触觉传感器
人工智能
计算机科学
电子皮肤
接口(物质)
机器人学
人机交互
手势
计算机硬件
材料科学
机器人
最大气泡压力法
气泡
纳米技术
并行计算
程序设计语言
作者
Ye Qiu,Zhiqiang Wang,Pengcheng Zhu,Binbin Su,Wei Chang,Ye Tian,Zheng Zhang,Herzl Chai,Aiping Liu,Liang Li,Huaping Wu
标识
DOI:10.1016/j.cej.2022.140890
摘要
Somatosensory networks that provide sophisticated sensory feedback and enable the dexterous manipulation of the human grasp remain difficult to replicate in robots, which is attributed to the grand challenge of densely covering the hand with tactile arrays. Here, a multisensory tactile glove is reported that is capable of object recognition with dense coverage of pressure and temperature sensing arrays. The synergistic effect of the multimodal configuration allows the tactile arrays to perceive contact pressure and thermal conductivity of an object involved in grasping motion, thus enhancing the accuracy via the combination of the mechanical features with thermal properties. By leveraging the multiple scanning technology and wireless transmission system, the tactile glove achieves a recognition accuracy of 94.2% in differentiating 20 types of objects with a modified deep learning algorithm. The large-area sensing arrays with high spatiotemporal resolution and multimodal sensing capabilities, which paves the way for the development of robot grasping tools, human–machine interfacing, and advanced prosthetics.
科研通智能强力驱动
Strongly Powered by AbleSci AI