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