PneuGelSight: Soft Robotic Vision-Based Proprioception and Tactile Sensing
Abstract
Soft pneumatic robot manipulators are popular in industrial and human-interactive applications due to their compliance and flexibility. However, deploying them in real-world scenarios requires advanced sensing for tactile feedback and proprioception. Our work presents a novel vision-based approach for sensorizing soft robots. We demonstrate our approach on PneuGelSight, a pioneering pneumatic manipulator featuring high-resolution proprioception and tactile sensing via an embedded camera. To optimize the sensor's performance, we introduce a comprehensive pipeline that accurately simulates its optical and dynamic properties, facilitating a zero-shot knowledge transition from simulation to real-world applications. PneuGelSight and our sim-to-real pipeline provide a novel, easily implementable, and robust sensing methodology for soft robots, paving the way for the development of more advanced soft robots with enhanced sensory capabilities.
Keywords
Cite
@article{arxiv.2508.18443,
title = {PneuGelSight: Soft Robotic Vision-Based Proprioception and Tactile Sensing},
author = {Ruohan Zhang and Uksang Yoo and Yichen Li and Arpit Agarwal and Wenzhen Yuan},
journal= {arXiv preprint arXiv:2508.18443},
year = {2026}
}
Comments
16 pages, 12 figures, International Journal of Robotics Research (accepted), 2025