Unlocking Dynamic Subtle Stimuli Tactile Perception: A Deep Learning‐Enhanced Super‐Resolution Tactile Sensor Array with Rapid Response

摘要

Human skin's touch perception, mediated by mechanoreceptors, can perceive tactile stimuli with a spatial resolution higher than the average spacing between mechanoreceptors, known as super‐resolution. This characteristic enables its sensitivity to both stimulus location and velocity. However, existing robotic tactile sensors lag behind human tactile perception, failing to achieve high spatial resolution and rapid response simultaneously. This significantly hinders robots from executing accurate, time‐sensitive interaction tasks, particularly during dynamic slight‐contact events. Here, a 130 μm‐thick flexible tactile sensor array is designed, with spatial resolution enhanced by a tailored deep learning model, multistage attention‐based adaptive spatial–temporal graph convolutional networks (MS‐AASTGCN), simultaneously achieving a dynamic response of ≈30 ms and a super‐resolution factor of 75.19. The tactile sensor array, based on single‐electrode triboelectric nanogenerators, can detect dynamic subtle stimuli. It features a bio‐inspired topological structure, facilitating super‐resolution performance while offering a large perception area with low sensor (taxel) density. Additionally, the MS‐AASTGCN enhances positioning resolution by extracting features fromsensing data and revealing the hidden relationships among taxels. This research provides new insights into haptic perception systems, enabling the execution of precise, time‐sensitive interaction tasks, such as tracking a bouncing table tennis ball.