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arXiv · 2605.08757

A Visuo-Tactile Data Collection System with Haptic Feedback for Coarse-to-Fine Imitation Learning

Yeseung Kim·Nayoung Oh·Jun Park·Teetat Thamronglak·Daehyung Park
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Abstract

We present a visuo-tactile data-collection system that generates temporally structured, contact-rich demonstrations for imitation learning. Conventional systems often decouple the operator from contact forces, which hinders the demonstration of subtle force modulation. Our system introduces a direct-drive gripper that the operator actuates with the fingers, preserving natural haptic feedback. Integrated visual sensors and custom tactile arrays capture image streams and contact geometry. A handle-mounted push button enables the operator to annotate the task's temporal structure in real time by marking task-critical regions. By fusing in-hand force perception with in-situ temporal annotation, the system produces multimodal datasets designed for coarse-to-fine learning algorithms that exploit structural task knowledge, enabling the development of high-quality manipulation policies.

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Yeseung Kim, Nayoung Oh, Jun Park, Teetat Thamronglak, Daehyung Park. 2026-05-09. A Visuo-Tactile Data Collection System with Haptic Feedback for Coarse-to-Fine Imitation Learning. https://arxiv.org/abs/2605.08757

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