Autor: |
Zhihao Zhu, Yingtian Xu, Waner Lin, Zhixian Hu, Zhuofan Lin, Zhenglong Sun, Zhengchun Peng, Ziya Wang |
Jazyk: |
angličtina |
Rok vydání: |
2023 |
Předmět: |
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Zdroj: |
Advanced Intelligent Systems, Vol 5, Iss 10, Pp n/a-n/a (2023) |
Druh dokumentu: |
article |
ISSN: |
2640-4567 |
DOI: |
10.1002/aisy.202300225 |
Popis: |
Perceiving surface characteristics through tactile interaction typically requires high‐resolution devices or precise spatial scanning to record and analyze a significant amount of information. However, most available tactile sensors require complicated technological processes, redundant layouts, and data acquisition circuits, which limits their ability to provide a real‐time static perception and feedback for potential applications such as robotic manipulation. Drawing inspiration from the sliding tactile (ST) perception mode of the human fingertip, a robust and flexible ST sensor with a low array density of 2.7 cells cm−2 is reported. This innovative sensor has a soft and cambered configuration that allows it to rapidly and accurately recognize the 3D surface features of objects, including grooves as small as 500 μm. Benefiting from the strong correlation between collected electronic responding and local deformation of sensing cell, the ST sensor can adaptively reconstruct surface patterns with the assistance of deep learning, even on unstructured objects. The pattern recognition system based on the robot is demonstrated by accurately classifying a set of mahjong tiles with nearly 100% accuracy, surpassing human tactile perception capabilities in the same task. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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