Design of a flexible tactile sensor for material and texture identification utilizing both contact-separation and surface sliding modes for real-life touch simulation

Abstract

Haptic feedback plays a crucial role, continuously offering individuals vital information about their external surroundings through physical contact. Therefore, rapid advances in human-friendly biomimetic electronics and flexible devices, have allowed the development of advance electronic skins for artificial haptic sensation. In particular, triboelectric nanogenerator-based tactile sensors have garnered significant interest, pursuing enhanced performance in material and texture recognition, coupled with simplicity in fabrication, cost-effectiveness, high resolution and sensitivity. Thus, in this work, we propose a flexible triboelectric tactile sensor, utilizing the freestanding single-electrode triboelectric nanogenerator principle, realizing concurrent material and texture detection in a single device. We leverage a novel hybrid operational regime for tactile sensing, combining the advantages of both contact-separation and surface sliding modes in a single contact-sliding-separation motion. This enables a realistic representation of the surface employing an artificial finger, by gathering material information from the contact-separation events and texture details from the sliding motion. Common materials such as wood, paper, copper and glass were used for the identification study along with textured surfaces made of the same materials with microscopic surface features. Simultaneous classification and recognition of materials and textures was performed by a single, 1D convolutional artificial neural network, achieving an average recognition accuracy of 98.4% across all different surfaces.