The automated assembly of complex products requires a system that can automatically plan a physically feasible sequence of actions for assembling many parts together. In this paper, we present ASAP, a physics-based planning approach for automatically generating such a sequence for general-shaped assemblies. ASAP accounts for gravity to design a sequence where each sub-assembly is physically stable with a limited number of parts being held and a support surface. We apply efficient tree search algorithms to reduce the combinatorial complexity of determining such an assembly sequence. The search can be guided by either geometric heuristics or graph neural networks trained on data with simulation labels. Finally, we show the superior performance of ASAP at generating physically realistic assembly sequence plans on a large dataset of hundreds of complex product assemblies. We further demonstrate the applicability of ASAP on both simulation and real-world robotic setups. Project website: asap.csail.mit.edu

翻译：复杂产品的自动化装配要求系统能够自动规划将多个零件组装在一起的物理可行性动作序列。本文提出ASAP，一种基于物理的规划方法，可自动为任意形状装配体生成此类序列。ASAP通过考虑重力因素设计装配序列，使每个子装配体在仅夹持有限数量零件且存在支撑表面的条件下保持物理稳定性。我们采用高效树搜索算法以降低确定此类装配序列的组合复杂度。该搜索可由几何启发式方法或基于仿真标签数据训练的图神经网络进行引导。最后，我们在包含数百个复杂产品装配体的大规模数据集上验证了ASAP生成物理真实装配序列规划的卓越性能，并通过仿真与真实机器人实验进一步展示了ASAP的适用性。项目网站：asap.csail.mit.edu