飞机结构装配中多机器人任务分配的高效调度算法
An Efficient Scheduling Algorithm for Multi-Robot Task Allocation in Assembling Aircraft Structures
摘要：
在飞机结构装配中有效利用协作机器人依赖于平衡机器人的工作量和确保无碰撞调度。我们把这个问题看作是在多个机器人之间分配大量重复的装配任务，如钻孔和安装紧固件。这样的任务分配通常被公式化为旅行商问题（TSP），这是NP难的，这意味着计算精确的最优解对于现实世界的应用来说在计算上是禁止的。间歇性的机器人故障需要实时任务重新分配，进一步加剧了问题的复杂性。在这封信中，我们提出了一种有效的方法，利用工件的几何形状和问题的结构，初步产生平衡和无冲突的机器人在标称条件下的时间表。随后，我们通过允许机器人首先完成其标称时间表，然后采用基于市场的优化器来分配剩余任务来处理故障。结果表明，在四个机器人系统上，与优化的贪婪多代理调度器相比，调度效率提高了11.5%，特别适用于需要数小时才能完成的飞机装配过程.此外，计算时间相似且较小，通常为数百毫秒。
英文摘要：
Efficient utilization of cooperating robots in the assembly of aircraft structures relies on balancing the workload of the robots and ensuring collision-free scheduling. We cast this problem as that of allocating a large number of repetitive assembly tasks, such as drilling holes and installing fasteners, among multiple robots. Such task allocation is often formulated as a Traveling Salesman Problem (TSP), which is NP-hard, implying that computing an exactly optimal solution is computationally prohibitive for real-world applications. The problem complexity is further exacerbated by intermittent robot failures necessitating real-time task reallocation. In this letter, we present an efficient method that exploits workpart geometry and problem structure to initially generate balanced and conflict-free robot schedules under nominal conditions. Subsequently, we deal with the failures by allowing the robots to first complete their nominal schedules and then employing a market-based optimizer to allocate the leftover tasks. Results show an improvement of 11.5\% in schedule efficiency as compared to an optimized greedy multi-agent scheduler on a four robot system, which is especially promising for aircraft assembly processes that take many hours to complete. Moreover, the computation times are similar and small, typically hundreds of milliseconds.
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