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

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 −1 (<50 kPa), linear sensitivity of 6.06 kPa −1 (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.