Biomimetic hydrogel-based sensors with dual-mode dynamic-static tactile sensing capability enabling robotic hand for intelligent material property recognition

Abstract

The realization of intelligent tactile perception in robotic systems requires multifunctional sensors capable of mimicking the dual-mode sensing mechanisms of human skin. Herein, we present a biomimetic hydrogel-based sensor capable of dynamic tactile detection through triboelectric sensing and static pressure monitoring via ionic-supercapacitive sensing. The triboelectric unit achieves a peak voltage of 14.64 V, with <5% signal decay over 5000 s of cycling, enabling robust detection of transient interactions (e.g., tapping or sliding). Additionally, the ionic-supercapacitive unit exhibits a high sensitivity of 2.69 kPa^-1 between 0.8–28 kPa, a rapid response time of 0.5 s, and minimal signal drift of <5% during 7-day continuous operation, providing stable monitoring of static interactions (e.g., touching or pressing). By leveraging a multilayer perceptron neural network, a robotic hand equipped with a biomimetic hydrogel-based bimodal sensor demonstrates intelligent recognition of material types and hardness levels with a high accuracy of 98.5%. This study establishes a paradigm for high-performance electronic skins, which advances human-machine interfaces and artificial intelligence-driven robotics through biomimetic tactile perception.

Keywords

dual-mode sensor / hydrogel / ionic sensing / material recognition / triboelectric sensing

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