Many fabric handling and 2D deformable material tasks in homes and industry require singulating layers of material such as opening a bag or arranging garments for sewing. In contrast to methods requiring specialized sensing or end effectors, we use only visual observations with ordinary parallel jaw grippers. We propose SLIP: Singulating Layers using Interactive Perception, and apply SLIP to the task of autonomous bagging. We develop SLIP-Bagging, a bagging algorithm that manipulates a plastic or fabric bag from an unstructured state, and uses SLIP to grasp the top layer of the bag to open it for object insertion. In physical experiments, a YuMi robot achieves a success rate of 67% to 81% across bags of a variety of materials, shapes, and sizes, significantly improving in success rate and generality over prior work. Experiments also suggest that SLIP can be applied to tasks such as singulating layers of folded cloth and garments. Supplementary material is available at https://sites.google.com/view/slip-bagging/.

翻译：摘要：在家庭和工业中，许多织物处理与二维可变形材料任务（如打开袋子或排列衣物以供缝纫）需要将材料层逐层分离。与依赖专用传感或末端执行器的方法不同，我们仅使用普通平行夹爪进行视觉观测。我们提出SLIP：基于交互感知的逐层分离方法，并将其应用于自主装袋任务。我们开发了SLIP-Bagging算法，该算法能够从无序状态操控塑料或织物袋，并利用SLIP抓取袋子的顶层以打开袋口，便于物体放入。在物理实验中，YuMi机器人针对多种材质、形状和尺寸的袋子实现了67%至81%的成功率，在成功率和泛化能力上较先前工作有显著提升。实验还表明，SLIP可应用于折叠布料与衣物的逐层分离等任务。补充材料见https://sites.google.com/view/slip-bagging/。