Mobile autonomous robots have the potential to revolutionize manufacturing processes. However, employing large robot fleets in manufacturing requires addressing challenges including collision-free movement in a shared workspace, effective multi-robot collaboration to manipulate and transport large payloads, complex task allocation due to coupled manufacturing processes, and spatial planning for parallel assembly and transportation of nested subassemblies. We propose a full algorithmic stack for large-scale multi-robot assembly planning that addresses these challenges and can synthesize construction plans for complex assemblies with thousands of parts in a matter of minutes. Our approach takes in a CAD-like product specification and automatically plans a full-stack assembly procedure for a group of robots to manufacture the product. We propose an algorithmic stack that comprises: (i) an iterative radial layout optimization procedure to define a global staging layout for the manufacturing facility, (ii) a graph-repair mixed-integer program formulation and a modified greedy task allocation algorithm to optimally allocate robots and robot sub-teams to assembly and transport tasks, (iii) a geometric heuristic and a hill-climbing algorithm to plan collaborative carrying configurations of robot sub-teams, and (iv) a distributed control policy that enables robots to execute the assembly motion plan collision-free. We also present an open-source multi-robot manufacturing simulator implemented in Julia as a resource to the research community, to test our algorithms and to facilitate multi-robot manufacturing research more broadly. Our empirical results demonstrate the scalability and effectiveness of our approach by generating plans to manufacture a LEGO model of a Saturn V launch vehicle with 1845 parts, 306 subassemblies, and 250 robots in under three minutes on a standard laptop computer.

翻译：移动自主机器人有潜力彻底改变制造过程。然而，在制造中部署大型机器人车队需解决共享工作空间中的无碰撞运动、有效操控与运输大型负载的多机器人协作、因耦合制造过程导致的复杂任务分配，以及嵌套子装配体的并行装配与运输的空间规划等挑战。我们提出一种用于大规模多机器人装配规划的全算法栈，该算法栈可应对这些挑战，并在数分钟内为包含数千个部件的复杂装配体合成建造方案。我们的方法以类计算机辅助设计的产品规格为输入，自动为一组机器人规划制造产品的全栈装配流程。该算法栈包括：(i) 迭代径向布局优化程序，用于定义制造设施的全局暂存布局；(ii) 图形修复混合整数规划公式及改进的贪心任务分配算法，用于最优分配机器人及机器人子团队至装配与运输任务；(iii) 几何启发式算法与爬山算法，用于规划机器人子团队的协作搬运构型；(iv) 分布式控制策略，使机器人能够无碰撞地执行装配运动规划。我们还提供在Julia中实现的开源多机器人制造模拟器作为研究社区的资源，以测试我们的算法并更广泛地促进多机器人制造研究。实验结果证明了方法的可扩展性与有效性：我们在标准笔记本电脑上，用不到三分钟生成了包含1845个部件、306个子装配体、由250个机器人制造的土星五号运载火箭乐高模型的规划方案。