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：许多家庭和工业中的织物处理及二维可变形材料任务，需要将材料层分离（如打开袋子或整理待缝纫的衣物）。不同于依赖专用传感器或末端执行器的方法，我们仅使用普通平行爪夹持器的视觉观测数据。我们提出SLIP：基于交互式感知的分层拆解方法，并将其应用于自主装袋任务。我们开发了SLIP-Bagging算法，该算法能处理非结构化状态的塑料或织物袋，通过SLIP抓取袋体顶层以打开袋口供物体放入。在物理实验中，YuMi机器人对多种材料、形状和尺寸的袋子实现了67%至81%的成功率，在成功率和通用性上显著超越先前工作。实验还表明SLIP可应用于折叠布料及衣物的分层拆解任务。补充材料详见https://sites.google.com/view/slip-bagging/。