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Capacitive in-sensor tactile computing

delete2025-07-01
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OA
AI
Y
Yan Chen
曹
曹杰 (Jie Cao)
J
Jie Qiu
D
Dongzi Yang
M
Mengyang Liu
M
Mengru Zhang
C
Chenyang Li
Z
Zhongyuan Wu
J
Jie Yu
张
张续勐 (Xumeng Zhang)
X
Xianzhe Chen
黄
黄张成 (Zhangcheng Huang)
E
Enming Song
王明 封面图
王明 (Ming Wang) *
刘
刘琦 (Qi Liu)
M
Ming Liu *
DOI:10.1038/s41467-025-60703-7delete
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摘要

摘要

En 中文
Real-time sensing and processing of tactile information are essential to enhance the capability of artificial electronic skins (e-skins), enabling unprecedented intelligent applications in tactile exploration and object manipulation. However, conventional tactile e-skin systems typically execute redundant data transfer and conversion for decision making due to their physical separation between sensors and processing units, leading to high transmission latency and power consumption. Here, we report an in-sensor tactile computing system based on a flexible capacitive pressure sensor array. This system utilizes multiple connected sensor networks to execute in-situ analog multiplication and accumulation operations, achieving both tactile sensing and computing functionalities. We experimentally implemented the in-sensor tactile computing system for low-level tactile sensory processing tasks including noise reduction and edge detection. The consumed power for single sensing-computing operation is over 22 times lower than that of a conventional mixed electronic system. These results demonstrate that our capacitive in-sensor computing system paves a promising way for power-constrained applications such as robotics and human-machine interfaces. Traditional tactile systems suffer from the physical separation between sensing and processing units, causing latency and power issues. Here, Chen et al. report a capacitive in-sensor tactile computing system, using sensor networks to execute in-situ multiplication and accumulation operations.
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期刊

Nature Communications 封面图
Nature Communications
IF:
15.7
论文数:
9.6W
被引数:
118.7W

机构

复旦大学 封面图
复旦大学
学者数:
7.2K
论文数: 1.9K
被引数: 3.2W
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