A Bioinspired Robotic Finger for Multimodal Tactile Sensing Powered by Fiber Optic Sensors

Abstract

The rapid advancement of soft robotic technology emphasizes the growing importance of tactile perception. Soft grippers, equipped with tactile sensing, can gather interactive information crucial for safe human–robot interaction, wearable devices, and dexterous manipulation. However, most soft grippers with tactile sensing abilities have limited modes of tactile perception, restricting their dexterity and safety. In addition, existing tactile systems are often complicated, leading to unstable perception signals. Inspired by various organisms, a novel multimodal tactile-sensing soft robotic finger is proposed. This finger, based on a modified fin ray structure, integrates a distributed fiber optic sensing system as part of its tactile sensory neural system. It replicates human finger capabilities, discerning contact forces as low as 0.01 N with exceptional sensitivity (106.96 mN nm⁻¹). Through training neural networks models, the finger achieves an accuracy exceeding 96% in recognizing roughness, material stiffness, and finger pad position. Assembled into two-finger parallel gripper, it demonstrates precise manipulation capabilities for fragile items like strawberries and potato chips. Moreover, through synergistic interplay of multimodal tactile sensing, this finger can successfully grasp an underwater transparent sphere, mitigating limitations of visual perception. The developed soft finger holds promise in various scenarios including hazardous environment detection and specialized grasping tasks.