Recent progress in high-resolution tactile sensor array: From sensor fabrication to advanced applications
作者机构：Research Institute for Frontier Science Beihang University School of Materials Science and Engineering Beihang University Key Laboratory of Intelligent Sensing Materials Chip Integration Technology of Zhejiang Province(2021E10022) Hangzhou Innovation Institute of Beihang University
出 版 物：《Progress in Natural Science:Materials International》 (自然科学进展·国际材料(英文))
年 卷 期：2023年第33卷第1期
页 面：55-66页
核心收录：
学科分类：080202[工学-机械电子工程] 08[工学] 0802[工学-机械工程]
基 金：supported by the National Key R&D Program of China[grant number 2018YFA0702100] the Zhejiang Provincial Key R&D Program of China [grant numbers 2021C05002, 2021C01026] the National Natural Science Foundation of China [grant number U21A2079] the Beijing Natural Science Foundation [grant number 2182032] the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang [grant number 2020R01007]
主 题：Tactile sensor arrays Fabrication Anti-crosstalk design Integration strategy Advanced application
摘 要：Tactile sensors can transform the environmental stimuli into electrical signals to perceive and quantify the environmental information, which show huge application prospects. The development of bionic robots and wearable devices towards intelligence has put high demands on the performance of tactile sensor arrays. Herein,the current state-of-the-art tactile sensor arrays over recent years have been summarized, from sensor array fabrication to advanced applications. The main preparation methods of patterned array including screen printing,3D printing, laser microprocessing, and textile technology are discussed in detail. Strategies to optimize the signal crosstalk caused by flexible high-density sensor arrays are systematically introduced from the perspective of structure design and circuit design. Furthermore, advanced tactile sensors are not limited to a single pressure sensing function, and hence the development of multimodal detection for sensors has been discussed. In order to promote the adaptability in applications, stretchable and self-powered versatile integration scheme for advanced sensing are briefly described. Then, by means of machine learning and neural networks, it is possible to deeply explore the information embedded in the tactile acquisition signal with enriched application scenarios. Finally,the current challenges and the future perspectives for flexible tactile sensor arrays towards practical use are provided.
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