Skin-inspired multi-modal mechanoreceptors for dynamic haptic exploration

Abstract

Active sensing is a fundamental aspect of human and animal interactions with the environment, providing essential information about the hardness, texture, and tackiness of objects. This ability stems from the presence of diverse mechanoreceptors in the skin, capable of detecting a wide range of stimuli and from the sensorimotor control of biological mechanisms. In contrast, existing tactile sensors for robotic applications typically excel in identifying only limited types of information, lacking the versatility of biological mechanoreceptors and the requisite sensing strategies to extract tactile information proactively. Here, inspired by human haptic perception, a skin-inspired artificial 3D mechanoreceptor (SENS) capable of detecting multiple mechanical stimuli is developed to bridge sensing and action in a closed-loop sensorimotor system for dynamic haptic exploration. A tensor-based non-linear theoretical model is established to characterize the 3D deformation (e.g., tensile, compressive, and shear deformation) of SENS, providing guidance for the design and optimization of multimode sensing properties with high fidelity. Based on SENS, a closed-loop robotic system capable of recognizing objects with improved accuracy (≈96%) is further demonstrated. This dynamic haptic exploration approach shows promise for a wide range of applications such as autonomous learning, healthcare, and space and deep-sea exploration.