Design of Flexible Tactile Electronic Skin Array Based on Magnetic Thin Films and Its Position-Sensing Applications

被引:1
|
作者
Zhang, Hui [1 ,2 ]
Weng, Ling [1 ,2 ]
Lin, Guoheng [1 ,2 ]
Li, Zhuolin [1 ,2 ]
Meng, Kai [1 ,2 ]
Jiang, Shengwang [1 ,2 ]
Zheng, Wendong [3 ]
机构
[1] Hebei Univ Technol, Sch Elect Engn, State Key Lab Reliabil & Intelligence Elect Equipm, Tianjin 300130, Peoples R China
[2] Hebei Univ Technol, Sch Elect Engn, Key Lab Electromagnet Field & Elect Apparat Reliab, Tianjin 300130, Peoples R China
[3] Tianjin Univ Technol, Sch Elect Engn & Automat, Tianjin 300384, Peoples R China
基金
中国国家自然科学基金;
关键词
Sensors; Robot sensing systems; Magnetic films; Skin; Magnetic sensors; Magnetic tunneling; Magnetic field measurement; Deep learning; e-skin; magnetic film; position-sensing; sensor array;
D O I
10.1109/JSEN.2024.3426078
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
To enable robots to perform precise operations, it is essential to equip them with extensive electronic skin to enhance their perceptual capabilities for sensing external information. Mimicking the structure of human skin, we have designed a flexible tactile electronic skin array capable of timely responses to external tactile stimuli. The electronic skin features a sandwich structure, comprising magnetic thin film, a silicone buffer layer, and tunnel magnetoresistive elements. Experiments on point pressure, point distance, and point angle are used to understand the basic characteristics of the magnetic sensing element, and the size of the position-sensing unit is determined with COMSOL simulation. The size of the array can be expanded as necessary, based on specific requirements and practical considerations. Based on the flexible tactile electronic skin array, we propose a novel position recognition method that utilizes the co-coupling of multiple magnetic sensing elements to determine the position information of contact forces. We designed a 10 x 10 grid experiment using convolutional neural networks (CNNs) to classify each grid position, and the results show a recognition accuracy of 91.2% and a resolution of 1 mm.
引用
收藏
页码:25541 / 25549
页数:9
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