A Representation of Cloth States based on a Derivative of the Gauss Linking Integral

Franco Coltraro, Josep Fontana, Jaume Amorós, Maria Alberich-Carramiñana, Júlia Borràs and Carme Torras

Applied Mathematics and Computation, 2023, vol. 457, issue C

Abstract: Robotic manipulation of cloth is a complex task because of the infinite-dimensional shape-state space of textiles, which makes their state estimation very difficult. In this paper we introduce the dGLI Cloth Coordinates, a finite low-dimensional representation of cloth states that allows us to efficiently distinguish a large variety of different folded states, opening the door to efficient learning methods for cloth manipulation planning and control. Our representation is based on a directional derivative of the Gauss Linking Integral and allows us to represent spatial as well as planar folded configurations in a consistent and unified way. The proposed dGLI Cloth Coordinates are shown to be more accurate in the representation of cloth states and significantly more sensitive to changes in grasping affordances than other classic shape distance methods. Finally, we apply our representation to real images of a cloth, showing that with it we can identify the different states using a distance-based classifier.

Keywords: Semantic state labelling; Robotic cloth manipulation; Deformable object representation and classification; Gauss Linking Integral (GLI) (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:457:y:2023:i:c:s009630032300334x

DOI: 10.1016/j.amc.2023.128165

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