触觉知觉
涂层
材料科学
触觉传感器
感知
人工智能
计算机科学
复合材料
机器人
神经科学
生物
作者
Shixin Zhang,Yiyong Yang,Fuchun Sun,Lei Bao,Jianhua Shan,Yuan Gao,Bin Fang
标识
DOI:10.1109/jsen.2024.3376574
摘要
Visuo-tactile skins (VTSs) are classified into coated-type, marker-type, and thermochromic-type. Coating wear resistance and spatial resolution are central issues for the coated-type VTS. This article proposes a wire-drawing process applied to the VTS to enhance the coating robustness. The wire-drawing coating has more stable mechanical properties, including high adhesion, adaptive deformation, and rupture resistance. Under different degrees of deformation, it can remain continuous and undamaged. In addition, the wire-drawing coating has a nanoscale particle distribution, whose microstructures are similar to the spraying coating to provide micron-scale spatial resolution. Via the wear resistance test, the wire-drawing coating has higher wear resistance than the spraying coating. Further, the VTS combined with a multitask learning model can identify textures and clothing properties of 18 different fabrics with more than 98% recognition accuracy. The results show that the VTS using the new process can provide highly learnable tactile data.
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