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Cloth detection and manipulation is a common task in domestic and industrialsettings, yet such tasks remain a challenge for robots due to clothdeformability. Furthermore, in many cloth-related tasks like laundry foldingand bed making, it is crucial to manipulate specific regions like edges andcorners, as opposed to folds. In this work, we focus on the problem ofsegmenting and grasping these key regions. Our approach trains a network tosegment the edges and corners of a cloth from a depth image, distinguishingsuch regions from wrinkles or folds. We also provide a novel algorithm forestimating the grasp location, direction, and directional uncertainty from thesegmentation. We demonstrate our method on a real robot system and show that itoutperforms baseline methods on grasping success. Video and other supplementarymaterials are available at: https://sites.google.com/view/cloth-segmentation.

Cloth Region Segmentation for Robust Grasp Selection