Multi-UAV Cost Optimization Method for Reliability-Aware Inspection

Unmanned aerial vehicles (UAVs) have advantages of rapidity and efficiency in inspection assignments. However, UAVs suffer from high costs and the difficulty of repairing faults. Thus, it is important to reduce the quantity of the UAVs used in tasks. To address the above challenges, this paper first establishes a correlation model to maximize the mission coverage rate as well as to minimize the quantity of UAVs. Then, a three-step method is designed by combining a genetic algorithm with the greedy algorithm to optimize the UAVs quantity and their paths. Finally, the UAVs without failure will be assigned to perform the unfinished tasks of the abnormal UAVs. Simulation results show that the method proposed in this paper can not only improve the mission coverage, but also minimize the quantity of the UAVs effectively.