Multi UAV cooperative task allocation method for intensive corridors of transmission lines inspection

Recently, with the rapid development of intensive corridors of transmission lines, Unmanned Aerial Vehicle (UAV) now meets new challenges in the inspection tasks of transmission lines. Although previous studies have achieved remarkable success in this field, they focused on the tasks of single UAV automatic inspection and UAV path planning, without considering multi-UAV collaborative inspection tasks. To solve these problems, we propose a novel improved genetic algorithm with multi-level chromosome hybrid coding and dual population selection, which is called CH&DS-GA. Specifically, based on the multi-traveling salesman problem (M-TSP), we established the multi-UAV traveling salesman problem model with charging stations (MU-TSP-C) and encouraged UAVs to select tasks adaptively according to the present power. In small-scale experiments, the CH&DS-GA can obtain approximate optimal solutions with little running time; in large-scale experiments, the relationship between the solution time and tasks are approximately linear as the tasks increase. The results demonstrate that the CH&DS-GA has superior performance.