Integrated sensing-memory-computing artificial tactile system based on force sensors and memristors

Recently, numerous artificial tactile systems have been developed to mimic human tactile, employing force sensors in combination with external memory and computing units. However, the separated architecture of force sensing, memory, and computing results in high power consumption and significant delays, which pose a significant challenge for the development of efficient artificial tactile systems. In this study, we propose an integrated sensing-memory-computing artificial tactile system (smcATS) consisting of a graphene-polystyrene microparticle (G-PsMp) force sensor and an Ag-Fe3O4-ITO memristor. The design of the Ag-Fe3O4-ITO memristor with cross-shaped electrodes addresses the issue of micrometer-scale electrodes in conventional memristors that cannot be directly connected to force sensors. Furthermore, the smcATS demonstrates excellent properties of switching, endurance, and resistance-retention. Based on this, we have developed a visualized smcATS with a resistance state visualization circuit, which can better mimic skin bruising caused by strong external forces. Most importantly, the smcATS can avoid the need for analog-to-digital conversion and data transfer between separate memory and computing units, providing an alternative perspective for developing more efficient artificial tactile systems.