Sub-Milliscale-Resolution Bimodal Tactile Sensor Array with Human-Skin-Like Graphesthesia Sensation.

Abstract

Multimodal sensory integration advances the development of embodied intelligent systems and robotics with human-skin-like tactile perception. However, the difficulties in simultaneously achieving high resolution and multimodality hamper the exquisite tactile perception to differentiate information through touching. In this study, we report a sub-milliscale-resolution bimodal tactile sensor array consisting of a piezoelectric sensor array for mapping pressure magnitude distribution and a triboelectric sensor array for contact height detection, enabling the calculation of Young's modulus distribution. As compared to existing studies, the bimodal tactile sensor array achieved sub-milliscale spatial resolution of 700 µm and relatively high sensor density of 226 pixels/cm², demonstrating fine-grained multimodal perception. By combining the pressure mapping information from the piezoelectric sensor array and contact height information from the triboelectric sensor array, with a rapid response time of 50 ms, the Young's modulus distribution can be revealed. Furthermore, the tactile sensor array can achieve human-skin-like graphesthesia sensation and reconstruct the softness-encrypted pattern with the assistance of deep learning algorithms, providing a paradigm-shift strategy of sub-milliscale-resolution tactile perception toward embodied intelligence and robotics.