车辆-无人机协同的调度和路径规划联合设计研究

In recent years, unmanned aerial vehicles (UAVs) are widely deployed in various domains. Due to limited flying range and communication distances, in practice we customarily use ground vehicles to assist UAVs in order to conquer the distance constraints. Efficient vehicle-drone cooperation can greatly optimize efficiency and save monetary costs. However, existing work only focuses on routing in two scenarios, vehicle-drone cooperative (point) inspection and parcel delivery, ignoring load balancing. In contrast, this project extends to three scenarios: point inspection, line inspection, and parcel delivery, wherein we systematically study both routing and scheduling in the vehicle-drone cooperation problem. Also, we further consider two realistic constraints which are ignored by prior work: synchronization and dynamics. To this end, this project comprehensively studies the joint design of scheduling and routing in the three scenarios under synchronization and dynamics constraints. It aims to propose a set of theoretical frameworks and implementation methods to jointly optimize scheduling and routing for vehicle-drone cooperation. The achievements of the project will stimulate the research on UAV-related areas and greatly promote the deployment of UAVs in various civilian and military applications.

近年来，对无人机的应用正快速推广至许多领域。然而，无人机的航程和通信距离都十分有限，因此，在各种应用中我们常使用车辆和无人机协同（车-机协同）来克服距离的限制，使其更加实用。高效的车-机协同能极大的优化时间、节省费用。然而，传统方法仅研究车-机协同巡检节点（巡点）和物流配送这两个场景，且往往只关注路径规划，忽视负载均衡。而本项目不仅扩展至巡点、巡线、配送三个场景，而且同时优化路径规划和任务调度。此外，我们还进一步考虑了现实场景下以往被忽视的两种约束：同步需求和动态环境。为此，本项目将针对三个场景下的车-机协同，从时间和空间两个维度出发，探索同步需求和动态环境对任务调度和路径设计的内在影响，并在此基础上提出车-机协同调度和路径规划联合设计的理论框架和实现方法。本项目的研究成果将有助于推动多个相关学科的交叉，并对推广无人机在各行各业的应用提供重要的技术储备和理论指导。

近年来，对无人机的应用正快速推广至许多领域。然而，无人机的航程和通信距离都十分有限，因此，在各种应用中我们常使用车辆和无人机协同（车-机协同）来克服距离的限制，使其更加实用。高效的车-机协同能极大的优化时间、节省费用。为此，本项目研究车辆和无人机协同的设施巡检和货物配送等应用的路径规划和任务调度联合设计问题。本项目从时间和空间两个维度出发，探索同步需求和动态环境对任务调度和路径设计的内在影响，并在此基础上提出车-机协同调度和路径规划联合设计的理论框架和实现方法。本项目的研究成果将有助于推动多个相关学科的交叉，并对推广无人机在各行各业的应用提供重要的技术储备和理论指导。