A robotic sensory system with high spatiotemporal resolution for texture recognition

Ningning Bai, Yiheng Xue, Shuiqing Chen, Lin Shi, Junli Shi, Yuan Zhang, Xingyu Hou, Kaixi Huang, Weidong Wang, Jin Zhang,

Nature Communications · 2023 · 209 citations · 45 references

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Concepts

TL;DR

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.

References

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