The Multi-UAV Path Planning for the Power Transmission Line Inspection

The power transmission line inspection is a key part of power system maintenance, and the safety and reliability of the power grid are closely related to the operation of transmission lines. To better plan the paths of unmanned aerial vehicles (UAVs) in large-scale inspection tasks, a novel two-stage algorithm is proposed in this work. Firstly, an improved K-means++ algorithm is proposed to assign the inspection tasks for multi-UAV. It considers the influence of the UAVs starting positions and improves the calculation of clustering centers. Then, the Q-learning based particle swarm optimization (QLPSO) algorithm is proposed to plan the inspection path for each UAV. It enhances the exploration of the particles by introducing the Q-leaning algorithm and the history information of the particles. Finally, the algorithm is tested on different-scaled inspection tasks. The results prove the effectiveness of the proposed algorithm in multi-UAV power transmission line inspection tasks.