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arXiv · 2501.16458

BiFold: Bimanual Cloth Folding with Language Guidance

Oriol Barbany·Adrià Colomé·Carme Torras
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Abstract

Cloth folding is a complex task due to the inevitable self-occlusions of clothes, their complicated dynamics, and the disparate materials, geometries, and textures that garments can have. In this work, we learn folding actions conditioned on text commands. Translating high-level, abstract instructions into precise robotic actions requires sophisticated language understanding and manipulation capabilities. To do that, we leverage a pre-trained vision-language model and repurpose it to predict manipulation actions. Our model, BiFold, can take context into account and achieves state-of-the-art performance on an existing language-conditioned folding benchmark. To address the lack of annotated bimanual folding data, we introduce a novel dataset with automatically parsed actions and language-aligned instructions, enabling better learning of text-conditioned manipulation. BiFold attains the best performance on our dataset and demonstrates strong generalization to new instructions, garments, and environments.

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Oriol Barbany, Adrià Colomé, Carme Torras. 2025-01-27. BiFold: Bimanual Cloth Folding with Language Guidance. https://arxiv.org/abs/2501.16458

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