Softness‐ and Pressure‐Perceptive Electronic Skin with Reservoir‐Computed Central Nervous System

Abstract Simultaneous detection of softness and tactile pressure emulates the ability of human skin to discern objects and their texture. This functionality is crucial for developing human‐interactive robots. Although electronic skin (e‐skin) devices have been designed to sense tactile pressure and temperature via flexible or stretchable films, only a few sensors with a complicated structure simultaneously measure softness with other stimuli. This study presents a reservoir‐computed, planar‐type pressure sensor‐integrated system, aiming to develop a simple, automated e‐skin capable of perceiving softness and pressure. Six tactile pressure sensors are integrated into a single horizontal row. When mounted on a curved platform and robotic hand, the sensor's contact area varies with the object's softness, altering the pressure distribution. An echo state network algorithm—a reservoir computing platform—is developed to analyze time‐series resistance data from the six sensors, enabling simultaneous softness and pressure prediction with high accuracy, analogous to the central nervous system. As a proof‐of‐concept, the sensor system is installed on a robotic hand, which demonstrates its ability to recognize softness and pressure. Owing to its simplicity, the sensor platform is adaptable to various tactile pressure sensors reported previously.