Gripping Positions Selection for Unfolding a Rectangular Cloth Product

Yamazaki, Kimitoshi

doi:10.1109/coase.2018.8560568

Cited by 5 publications

(2 citation statements)

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“…[11] uses the YOLO detection network to detect the thickest folded edge and grasp a folded towel from a stack. [8] uses an autoencoder network to predict the real edges of towels. This is similar to our approach; however, their method trains a network to output latent features and performs nearest-neighbor classification on input features to predict good grasp points, whereas our network directly outputs segmentation masks of grasp regions and also determines good grasp directions.…”

Section: A Cloth Perceptionmentioning

confidence: 99%

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Cloth Region Segmentation for Robust Grasp Selection

Qian,

Weng,

Zhang

et al. 2020

Preprint

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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.

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Section: A Cloth Perceptionmentioning

confidence: 99%

“…Robotic cloth manipulation is a well-studied domain with a variety of unsolved tasks, including laundry folding [1], [2], laundry unfolding or smoothing [3], [4], [5], [6], [7], [8], bed making [9], [10], and grasping [11], [12], [13].…”

Section: A Cloth Perceptionmentioning

confidence: 99%