Due to the development needs of the intelligent manufacturing industry, the use of drones is expanding indefinitely, and at the same time, extremely high requirements are imposed on the autonomous navigation of drones to reduce human intervention. This paper presents an UAV/ UGV scheduling problem in which the UAV needs to be recharged by the UGV in order to working in persistent tasks, and meanwhile, the UGV need to visits UGV working depots. Two different problem are presented: fixed charging sets problem (FCSP) and discrete charging sets problem (DCSP). In FCSP, charging sets are fixed, and a two-stage travelling salesman problem method is proposed to solve the problem. DCSP is a modification of FCSP while charging segments are discrete into serval segments, an graph transformation approach was proposed to transform DCSP into GTSP, so DCSP can be resolved by using GTSP solvers. Simulation results shows that both DCSP and FCSP can ensure UAV/UGV work in persistent tasks, and the graph transformation algorithm can efficiently transform DCSP into GTSP.

中文翻译：

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智能制造中UAV / UGV协作系统的路径规划

由于智能制造业的发展需求，无人机的使用正在无限扩展，同时，对无人机的自主导航提出了很高的要求，以减少人为干预。本文提出了一个无人机/ UGV调度问题，其中UGV需要对UAV充电才能执行持续性任务，同时UGV需要访问UGV工作库。提出了两个不同的问题：固定计费集问题（FCSP）和离散计费集问题（DCSP）。在FCSP中，计费集是固定的，并提出了一种两阶段旅行商问题解决方法。DCSP是FCSP的一种改进，将收费段离散为服务段，提出了一种图变换方法将DCSP转换为GTSP，因此可以使用GTSP求解器来解析DCSP。仿真结果表明，DCSP和FCSP均可确保UAV / UGV在持久性任务中工作，图变换算法可将DCSP高效地转换为GTSP。