# UltraTac: Integrated Ultrasound-Augmented Visuotactile Sensor for Enhanced Robotic Perception

**Authors:** Junhao Gong, Kit-Wa Sou, Shoujie Li, Changqing Guo, Yan Huang, Chuqiao Lyu, Ziwu Song, Wenbo Ding

arXiv: 2508.20982 · 2025-09-01

## TL;DR

UltraTac is a novel integrated sensor combining visuotactile imaging and ultrasound sensing, enabling enhanced perception of object features, material classification, and texture recognition for robotic applications.

## Contribution

The paper introduces UltraTac, a coaxial optoacoustic sensor that unifies visuotactile and ultrasound sensing without performance trade-offs, and demonstrates its effectiveness in robotic perception tasks.

## Key findings

- Proximity sensing with R^2=0.90 in 3-8 cm range
- Material classification accuracy of 99.20%
- Texture-material object recognition at 92.11% accuracy

## Abstract

Visuotactile sensors provide high-resolution tactile information but are incapable of perceiving the material features of objects. We present UltraTac, an integrated sensor that combines visuotactile imaging with ultrasound sensing through a coaxial optoacoustic architecture. The design shares structural components and achieves consistent sensing regions for both modalities. Additionally, we incorporate acoustic matching into the traditional visuotactile sensor structure, enabling integration of the ultrasound sensing modality without compromising visuotactile performance. Through tactile feedback, we dynamically adjust the operating state of the ultrasound module to achieve flexible functional coordination. Systematic experiments demonstrate three key capabilities: proximity sensing in the 3-8 cm range ($R^2=0.90$), material classification (average accuracy: 99.20%), and texture-material dual-mode object recognition achieving 92.11% accuracy on a 15-class task. Finally, we integrate the sensor into a robotic manipulation system to concurrently detect container surface patterns and internal content, which verifies its potential for advanced human-machine interaction and precise robotic manipulation.

## Full text

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## Figures

12 figures with captions in the complete paper: https://tomesphere.com/paper/2508.20982/full.md

## References

32 references — full list in the complete paper: https://tomesphere.com/paper/2508.20982/full.md

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Source: https://tomesphere.com/paper/2508.20982