Skin‐Inspired Bimodal Receptors for Object Recognition and Temperature Sensing Simulation

摘要

Abstract Skin contacts with objects with different thermal conductivity and tactile perception will produce different temperature and tactile sensations. Here, an innovative creation is presented known as the BB‐Skin, a highly realistic bionic bimodal electronic skin, meticulously designed to mirror the thermal sensitivity and tactile perception found in human skin. This technology allows for precise object recognition and offers remote temperature sensing feedback. The BB‐Skin comprises temperature sensing, heating, and tribo‐electrode modules. Through the utilization of machine learning algorithms that measure the thermal conductivity and electronegativity of materials, a bimodal bionic robot object recognition system is developed, achieving an impressive accuracy rate exceeding 98.11%. The bimodal nature of the system, based on different types of electrical signals that operate independently, significantly enhances the reliability of the device. Moreover, harnessing the inherent capabilities of the BB‐Skin, a novel remote temperature sensing and feedback system is successfully implemented. This system adeptly replicates the temperature perception when remotely touching objects and provides users with feedback through gloves embedded with heating and cooling modules.