In multi-agent applications such as surveillance and logistics, fleets of mobile agents are often expected to coordinate and safely visit a large number of goal locations as efficiently as possible. The multi-agent planning problem in these applications involves allocating and sequencing goals for each agent while simultaneously producing conflict-free paths for the agents. In this article, we introduce a new algorithm called MS* which computes an optimal solution for this multi-agent problem by fusing and advancing state of the art solvers for multi-agent path finding (MAPF) and multiple travelling salesman problem (mTSP). MS* leverages our prior subdimensional expansion approach for MAPF and embeds the mTSP solvers to optimally allocate and sequence goals for agents. Numerical results show that our new algorithm can solve the multi-agent problem with 20 agents and 50 goals in a minute of CPU time on a standard laptop.
翻译:在监测和后勤等多试剂应用中,机动剂车队通常要尽可能高效地协调和安全地访问大量目标地点,这些应用中的多剂规划问题涉及为每个剂分配和排序目标,同时为剂制造无冲突路径。在本篇文章中,我们引入了一种名为MS* 的新算法,该算法计算出解决这一多剂问题的最佳办法,方法是在多剂路径发现和多次流动销售人员问题中引信和推进先进的解答器。MS* 利用我们以前对MAPF的次维扩展方法,并嵌入MTSP解答器,以便最佳地分配和排序各剂的目标。数字结果显示,我们的新算法可以在标准手提电脑上的CPU时间一分钟内用20个剂和50个目标解决多剂问题。