A high-accuracy, real-time, intelligent material perception system with a machine-learning-motivated pressure-sensitive electronic skin

Developing e-skins that can perceive stimuli with high sensitivity and material recognition functionality at low cost is of great importance to intelligent perception. Here, a hybrid e-skin (PTES) consisting of a triboelectric nanogenerator in tandem with a piezoresistive pressure sensor (PPS) is reported by using an eggshell membrane and infiltration method, which effectively perceives static and dynamic tactile information, such as human physiological information, manipulator tactile sensation, and human walking state. By integrating PTES with a high-speed data collector and machine learning, a material perception system capable of recognizing 12 materials in real time within one touch is established. A PTES array that can detect material property and location further demonstrates the feasibility of simultaneously processing multidimensional information. Additionally, by paralleling with a thin-film resistor, the PPS achieves an ultra-high sensitivity that can also be linearly adjusted. This PTES can open a new avenue for practical intelligent perception and realization of prominent applications.