A representation of cloth states based on a derivative of the Gauss Linking Integral

Journal Article (2023)


Applied Mathematics and Computation





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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 al- lows 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.


learning (artificial intelligence), pose estimation.

Author keywords

Cloth manipulation, topological representation

Scientific reference

F. Coltraro, J. Fontana, J. Amorós, M. Alberich-Carramiñana, J. Borràs and C. Torras. A representation of cloth states based on a derivative of the Gauss Linking Integral. Applied Mathematics and Computation, 457: 128165, 2023.