Rapid tactile processing is one of the most effective and direct strategies for robots to interact with surrounding environment. However, achieving both fast and accurate tactile recognition remains a challenge due to the inherent trade-off between sensor sensitivity and reaction time. In this study, we developed a bioinspired textured sensor array (TSA) using a circular grid arrangement, which could provide rich information on dynamic tactile processes in a self-powered manner. Early tactile process model (ETPM) was introduced to prioritize early-stage tactile data, which enables ultrafast decision-making speed without compromising classification accuracy. Specifically, our system achieved early predictions of object classification with an accuracy of 92 % while using only the initial 19 % (48 ms) of tactile data. The practicability of this system was examined through integration into a robotic arm. An ultrafast reaction time of 89 ms was achieved in real-time object property prediction, which is even faster than human hands. This advancement provides a robust foundation for rapid and precise tactile recognition in robotic perception systems, improving the robot’s response speed, reliability, and intelligence in real-world applications, including collaborative manufacturing, assistive technologies, and interactive service environments.
