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基于人工智能启发的全织物仿生电子皮肤的直觉和触觉双模感知用于智能材料感知。

Intuition-and-Tactile Bimodal Sensing Based on Artificial-Intelligence-Motivated All-Fabric Bionic Electronic Skin for Intelligent Material Perception.

机构信息

School of Microelectronics, Shandong University, Jinan, 250101, China.

RFIC Centre, Kwangwoon University, Seoul, 01897, South Korea.

出版信息

Small. 2024 Apr;20(14):e2308127. doi: 10.1002/smll.202308127. Epub 2023 Nov 27.

Abstract

Developing electronic skins (e-skins) with extraordinary perception through bionic strategies has far-reaching significance for the intellectualization of robot skins. Here, an artificial intelligence (AI)-motivated all-fabric bionic (AFB) e-skin is proposed, where the overall structure is inspired by the interlocked bionics of the epidermis-dermis interface inside the skin, while the structural design inspiration of the dielectric layer derives from the branch-needle structure of conifers. More importantly, AFB e-skin achieves intuition sensing in proximity mode and tactile sensing in pressure mode based on the fringing and iontronic effects, respectively, and is simulated and verified through COMSOL finite element analysis. The proposed AFB e-skin in pressure mode exhibits maximum sensitivity of 15.06 kPa (<50 kPa), linear sensitivity of 6.06 kPa (50-200 kPa), and fast response/recovery time of 5.6 ms (40 kPa). By integrating AFB e-skin with AI algorithm, and with the support of material inference mechanisms based on dielectric constant and softness/hardness, an intelligent material perception system capable of recognizing nine materials with indistinguishable surfaces within one proximity-pressure cycle is established, demonstrating abilities that surpass human perception.

摘要

通过仿生策略开发具有卓越感知能力的电子皮肤(e-skins),对机器人皮肤的智能化具有深远的意义。在这里,提出了一种人工智能(AI)驱动的全织物仿生(AFB)电子皮肤,其整体结构灵感来自皮肤内部表皮-真皮界面的联锁仿生,而介电层的结构设计灵感则源自针叶树的树枝状针结构。更重要的是,AFB 电子皮肤基于边缘场和离子电导效应,分别实现了接近模式下的直觉感知和压力模式下的触觉感知,并通过 COMSOL 有限元分析进行了模拟和验证。所提出的压力模式下的 AFB 电子皮肤在 50kPa 以下的压力范围内具有最大灵敏度 15.06kPa、线性灵敏度 6.06kPa,以及快速响应/恢复时间 5.6ms。通过将 AFB 电子皮肤与 AI 算法集成,并利用基于介电常数和柔软度/硬度的材料推理机制,建立了一种能够在一次接近-压力循环内识别九种表面难以区分的材料的智能材料感知系统,展示了超越人类感知能力的能力。

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