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电容式内置传感器触觉计算

Capacitive in-sensor tactile computing.

作者信息

Chen Yan, Cao Jie, Qiu Jie, Yang Dongzi, Liu Mengyang, Zhang Mengru, Li Chenyang, Wu Zhongyuan, Yu Jie, Zhang Xumeng, Chen Xianzhe, Huang Zhangcheng, Song Enming, Wang Ming, Liu Qi, Liu Ming

机构信息

State Key Laboratory of Integrated Chips and Systems, Frontier Institute of Chip and System, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.

College of Integrated Circuits and Micro-Nano Electronics, Fudan University, Shanghai, China.

出版信息

Nat Commun. 2025 Jul 1;16(1):5691. doi: 10.1038/s41467-025-60703-7.

Abstract

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.

摘要

实时感知和处理触觉信息对于增强人工电子皮肤(e-皮肤)的能力至关重要,能够在触觉探索和物体操纵方面实现前所未有的智能应用。然而,传统的触觉e-皮肤系统由于传感器和处理单元之间的物理分离,通常会执行冗余的数据传输和转换以进行决策,从而导致高传输延迟和功耗。在此,我们报道了一种基于柔性电容式压力传感器阵列的传感器内触觉计算系统。该系统利用多个相连的传感器网络执行原位模拟乘法和累加运算,实现触觉传感和计算功能。我们通过实验实现了用于低层次触觉传感处理任务(包括降噪和边缘检测)的传感器内触觉计算系统。单次传感-计算操作的功耗比传统混合电子系统低22倍以上。这些结果表明,我们的电容式传感器内计算系统为机器人技术和人机接口等功率受限应用铺平了一条充满希望的道路。

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