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需要一个能够自动规划多部件装配的物理可行动作序列的系统。本文提出ASAP——一种基于物理的规划方法，用于自动生成通用形状装配体的序列。ASAP考虑重力因素，设计在仅固定少数部件且存在支撑面的情况下每个子装配体均保持物理稳定的序列。我们采用高效的树搜索算法来降低确定此类装配序列的组合复杂度。搜索过程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引导。最后，我们在包含数百个复杂产品装配体的大型数据集上展示了ASAP生成物理真实装配序列计划的优越性能。进一步地，我们通过仿真和真实机器人实验验证了ASAP的适用性。项目网站：asap.csail.mit.edu