A robotic sensory system with high spatiotemporal resolution for texture recognition

TLDR

Humans identify objects by sliding a finger, capturing static pressure and high‑frequency vibrations, whereas current robotic sensors detect pressure, shear, and strain but lack simultaneous high‑frequency response or require multiple sensors. The study presents a real‑time artificial sensory system using a single iontronic slip‑sensor for high‑accuracy texture recognition and introduces spatiotemporal resolution as a criterion linking sensing performance to recognition. The slip‑sensor detects static and dynamic stimuli from 0 to 400 Hz with 15 μm spatial spacing, 6 μm height, and 0.02 Hz frequency resolution at 400 Hz, allowing precise discrimination of fine surface features. When mounted on a prosthetic fingertip, the system identified 20 commercial textiles with 100 % accuracy at a fixed sliding rate and 98.9 % at random rates, demonstrating potential for subtle tactile sensation in robotics, prosthetics, and haptic virtual reality.

Abstract

Abstract Humans can gently slide a finger on the surface of an object and identify it by capturing both static pressure and high-frequency vibrations. Although modern robots integrated with flexible sensors can precisely detect pressure, shear force, and strain, they still perform insufficiently or require multi-sensors to respond to both static and high-frequency physical stimuli during the interaction. Here, we report a real-time artificial sensory system for high-accuracy texture recognition based on a single iontronic slip-sensor, and propose a criterion—spatiotemporal resolution, to corelate the sensing performance with recognition capability. The sensor can respond to both static and dynamic stimuli (0-400 Hz) with a high spatial resolution of 15 μm in spacing and 6 μm in height, together with a high-frequency resolution of 0.02 Hz at 400 Hz, enabling high-precision discrimination of fine surface features. The sensory system integrated on a prosthetic fingertip can identify 20 different commercial textiles with a 100.0% accuracy at a fixed sliding rate and a 98.9% accuracy at random sliding rates. The sensory system is expected to help achieve subtle tactile sensation for robotics and prosthetics, and further be applied to haptic-based virtual reality and beyond.