Design of AI-Enhanced and Hardware-Supported Multimodal E-Skin for Environmental Object Recognition and Wireless Toxic Gas Alarm

Abstract Post-earthquake rescue missions are full of challenges due to the unstable structure of ruins and successive aftershocks. Most of the current rescue robots lack the ability to interact with environments, leading to low rescue efficiency. The multimodal electronic skin (e-skin) proposed not only reproduces the pressure, temperature, and humidity sensing capabilities of natural skin but also develops sensing functions beyond it—perceiving object proximity and NO 2 gas. Its multilayer stacked structure based on Ecoflex and organohydrogel endows the e-skin with mechanical properties similar to natural skin. Rescue robots integrated with multimodal e-skin and artificial intelligence (AI) algorithms show strong environmental perception capabilities and can accurately distinguish objects and identify human limbs through grasping, laying the foundation for automated post-earthquake rescue. Besides, the combination of e-skin and NO 2 wireless alarm circuits allows robots to sense toxic gases in the environment in real time, thereby adopting appropriate measures to protect trapped people from the toxic environment. Multimodal e-skin powered by AI algorithms and hardware circuits exhibits powerful environmental perception and information processing capabilities, which, as an interface for interaction with the physical world, dramatically expands intelligent robots’ application scenarios.