AI‐Enhanced Bionic Aquatic E‐Skin Enables Precise Capture of Minimal Tactile Differences Toward Undisturbed Underwater Interaction

Future marine exploitation requires underwater robots with reliable tactile perception. However, existing underwater haptic sensing technology remains challenged in discriminating similar physical properties among objects owing to strong hydrodynamic noise. Herein, we propose a triboelectric aquatic electronic skin (E-skin) capable of decoupling tactile signatures arising from minimal differences in unsteady water flow and high hydrostatic pressure disturbance. This is achieved through a bioinspired fish lateral line mechanical design that integrates a bionic fish-scale array to attenuate flow impact, thermoplastic polyurethane (TPU) powders to withstand hydrostatic compression, and an ionic hydrogel with asymmetric ion pairs to enhance signal output. The aquatic E-skin exhibits high sensitivity to tiny vibrations caused by surface differences when sliding over objects. Leveraging a feature-fusion machine learning, it extracts robust tactile vibrations during water flow motion and precisely classifies underwater minimal differences in texture and hardness, as well as roughness from 0.8 to 1600 µm. Additionally, integration of the E-skin on a robotic fish demonstrates its potential in fish swimming state detection to achieve intelligent aquaculture. This AI-enhanced E-skin not only enhances the reliability of underwater minimal difference perception but also unlocks novel interaction capabilities for broad marine applications in disturbance-rich aquatic environments.