PneuGelSight: Soft Robotic Vision-Based Proprioception and Tactile Sensing

Fuente: arXiv
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Hauptverfasser: Zhang, Ruohan, Yoo, Uksang, Li, Yichen, Agarwal, Arpit, Yuan, Wenzhen
Format: Preprint
Veröffentlicht: 2025
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author Zhang, Ruohan
Yoo, Uksang
Li, Yichen
Agarwal, Arpit
Yuan, Wenzhen
author_facet Zhang, Ruohan
Yoo, Uksang
Li, Yichen
Agarwal, Arpit
Yuan, Wenzhen
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2508_18443
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle PneuGelSight: Soft Robotic Vision-Based Proprioception and Tactile Sensing
Zhang, Ruohan
Yoo, Uksang
Li, Yichen
Agarwal, Arpit
Yuan, Wenzhen
Robotics
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.
title PneuGelSight: Soft Robotic Vision-Based Proprioception and Tactile Sensing
topic Robotics
url https://arxiv.org/abs/2508.18443