Robotic manipulation of cloth is a highly complex task because of its infinite-dimensional shape-state space that makes cloth state estimation very difficult. In this paper we introduce the dGLI Cloth Coordinates, a low-dimensional representation of the state of a rectangular piece of cloth that allows to efficiently distinguish key topological changes in a folding sequence, 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 both planar and spatial configurations in a consistent unified way. The proposed dGLI Cloth Coordinates are shown to be more accurate in the classification 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 we can identify the different states using a simple distance-based classifier.

通过介绍dGLI布料坐标系，本文为布料操作规划和控制提供了高效的学习方法，其基于高斯连接积分的方向导数允许一致性统一地表示平面和空间配置。该坐标系在分类布料状态和感知抓把变化等方面表现更加精准灵敏，且被证明可以通过简单的距离分类器来识别不同的状态。

dGLI布料坐标：基于拓扑表示的布料状态语义分类