| Summary: | The last decade has witnessed unmanned aerial vehicles (UAVs) emerging as a powerful platform for various industrial and civilian applications. However, refrained by limited battery capacities, the hovering time of UAVs is still limited, impeding them from achieving remote tasks, such as wide area inspection. To deal with such long-range applications, a common sense solution is to employ vehicles to transport, launch, and recycle UAVs. Efficient routing and scheduling for UAVs and vehicles can greatly reduce time consumption and financial expenses incurred in long-range inspection. Nevertheless, prior works in vehicle-assisted UAV inspection considered only one UAV, and was incapable of concurrently serving multiple targets distributed in an area. Leveraging multiple UAVs to serve multiple targets in parallel can significantly enhance efficiency and expand service areas. Therefore, in this paper, we propose a novel hybrid genetic algorithm (HGA), which supports the cooperation of one vehicle and multiple drones for wide area inspection applications. HGA allows multiple UAVs to launch and recycle in different locations, minimizing time wastage for both the vehicle and UAVs. Performance evaluation is presented to demonstrate the effectiveness and efficiency of our algorithm when compared with existing solutions.
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