Cloth Funnels: Canonicalized-Alignment for Multi-Purpose Garment Manipulation

Canberk, Alper; Cheng, C. H.; Ha, Huy Thuc; Burchfiel, Benjamin; Cousineau, Eric; Feng, Siyuan; Song, Shuran

doi:10.1109/icra48891.2023.10161546

Cited by 10 publications

References 25 publications

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ShakingBot: dynamic manipulation for bagging

Gu,

Zhang,

et al. 2024

Robotica

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Bag manipulation through robots is complex and challenging due to the deformability of the bag. Based on the dynamic manipulation strategy, we propose a new framework, ShakingBot, for the bagging tasks. ShakingBot utilizes a perception module to identify the key region of the plastic bag from arbitrary initial configurations. According to the segmentation, ShakingBot iteratively executes a novel set of actions, including Bag Adjustment, Dual-arm Shaking, and One-arm Holding, to open the bag. The dynamic action, Dual-arm Shaking, can effectively open the bag without the need to take into account the crumpled configuration. Then, the robot inserts the items and lifts the bag for transport. We perform our method on a dual-arm robot and achieve a success rate of 21/33 for inserting at least one item across various initial bag configurations. In this work, we demonstrate the performance of dynamic shaking action compared to the quasi-static manipulation in the bagging task. We also show that our method generalizes to variations despite the bag’s size, pattern, and color. Supplementary material is available at https://github.com/zhangxiaozhier/ShakingBot.

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ShakingBot: dynamic manipulation for bagging

Gu,

Zhang,

et al. 2024

Robotica

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FabricFolding: learning efficient fabric folding without expert demonstrations

He,

Meng,

Sun

et al. 2024

Robotica

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Autonomous fabric manipulation is a challenging task due to complex dynamics and potential self-occlusion during fabric handling. An intuitive method of fabric-folding manipulation first involves obtaining a smooth and unfolded fabric configuration before the folding process begins. However, the combination of quasi-static actions like pick & place and dynamic action like fling proves inadequate in effectively unfolding long-sleeved T-shirts with sleeves mostly tucked inside the garment. To address this limitation, this paper introduces an enhanced quasi-static action called pick & drag, specifically designed to handle this type of fabric configuration. Additionally, an efficient dual-arm manipulation system is designed in this paper, which combines quasi-static (including pick & place and pick & drag) and dynamic fling actions to flexibly manipulate fabrics into unfolded and smooth configurations. Subsequently, once it is confirmed that the fabric is sufficiently unfolded and all fabric keypoints are detected, the keypoint-based heuristic folding algorithm is employed for the fabric-folding process. To address the scarcity of publicly available keypoint detection datasets for real fabric, we gathered images of various fabric configurations and types in real scenes to create a comprehensive keypoint dataset for fabric folding. This dataset aims to enhance the success rate of keypoint detection. Moreover, we evaluate the effectiveness of our proposed system in real-world settings, where it consistently and reliably unfolds and folds various types of fabrics, including challenging situations such as long-sleeved T-shirts with most parts of sleeves tucked inside the garment. Specifically, our method achieves a coverage rate of 0.822 and a success rate of 0.88 for long-sleeved T-shirts folding. Supplemental materials and dataset are available on our project webpage at https://sites.google.com/view/fabricfolding.

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DeFNet: deconstructed strategy for multi-step fabric folding tasks

Gu,

He,

2024

The Journal of The Textile Institute

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Cloth Funnels: Canonicalized-Alignment for Multi-Purpose Garment Manipulation

Cited by 10 publications

References 25 publications

ShakingBot: dynamic manipulation for bagging

ShakingBot: dynamic manipulation for bagging

FabricFolding: learning efficient fabric folding without expert demonstrations

DeFNet: deconstructed strategy for multi-step fabric folding tasks

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