Effective planning of long-horizon deformable object manipulation requires
suitable abstractions at both the spatial and temporal levels. Previous methods
typically either focus on short-horizon tasks or make strong assumptions that
full-state information is available, which prevents their use on deformable
objects. In this paper, we propose PlAnning with Spatial-Temporal Abstraction
(PASTA), which incorporates both spatial abstraction (reasoning about objects
and their relations to each other) and temporal abstraction (reasoning over
skills instead of low-level actions). Our framework maps high-dimension 3D
observations such as point clouds into a set of latent vectors and plans over
skill sequences on top of the latent set representation. We show that our
method can effectively perform challenging sequential deformable object
manipulation tasks in the real world, which require combining multiple tool-use
skills such as cutting with a knife, pushing with a pusher, and spreading the
dough with a roller.

本文提出了一种采用空间 - 时间抽象进行场景感知的长时程变形物体操作规划框架（PASTA），其将高维 3D 观测映射到一组潜变量上，生成技能序列，能够在真实环境中快速地、有效地执行复杂的变形物体操纵任务，需要组合刀具使用技能、推力器推动技能和滚筒铺面技能。