Return Path Planning for UAVs in Mountainous Power Transmission Line Inspection Based on an Improved Grey Wolf Optimization Algorithm

UAVs are widely used for power transmission line inspection in remote mountainous areas. However, during the return flight, accidents such as crashes frequently occur due to the complex terrain and flight environment, severely impacting the safety and efficiency of inspection tasks. To address this issue, this paper proposes an Improved Grey Wolf Optimization (IGWO) algorithm aimed at optimizing the UAV return path planning task. The algorithm enhances global search ability and convergence speed by introducing Fuch chaotic mapping for population initialization and a secondary reverse learning strategy. In benchmark function optimization experiments, IGWO performed excellently across multiple test functions, demonstrating its strong global search capabilities and rapid convergence. In the path planning experiment for Environment 1, the path planned by IGWO only increased by 1.4% compared to the straight-line distance, while in Environment 2, the path length increased by only 3.3%. The results indicate that IGWO not only optimizes the safety of the path but also significantly improves flight efficiency and reduces flight distance, showing its broad application prospects in complex mountainous environments.