Bimodal iontronic skins powered by edge intelligence for real-time collaborative interaction

Abstract Real-time sensing and processing of large-scale tactile information are crucial for enhancing the compliant interaction of embodied robots, especially in collaborative systems. However, existing robotic skin systems are limited by latency in high-throughput signal readout and intelligent reasoning, making robust real-time interaction challenging. Here, we present a flexible bimodal skin powered by edge intelligence, enabling real-time sensory perception, decision-making, and actuation based on large-area coverage. The modular bimodal skin integrates pressure and temperature sensors, providing full coverage on robotic arm with over 768 pressure and 75 temperature sensor units. A rapid, crosstalk-free readout interface is implemented using a frequency-encoding architecture. Furthermore, we develop a lightweight deep learning framework that enables real-time autonomous decision-making for the bimodal skin at the edge device. We demonstrate that our system facilitates smooth, adaptive interaction for individuals with mobility impairments, even under complex or emergency conditions. This technology opens a promising avenue for real-time perception and interaction in human-centered embodied robotics.