Abstract: In recent years, as the scale of transmission networks continues to expand, inspection tasks have become increasingly demanding. To address challenges such as obstacle avoidance difficulties and poor path smoothness encountered by single drones during local inspections in complex environments, this paper proposes a three-dimensional environment model based on grid representation and expanded safety boundaries. A 3D path planning method combining an improved genetic algorithm with the dynamic window approach (IGA-DWA) is introduced. The global path optimization is achieved using the genetic algorithm, while dynamic obstacles" trajectories are predicted via an extended Kalman filter, enabling safe flight under both static and dynamic disturbances. Simulation results show that, in complex 3D environments, the proposed IGA-DWA algorithm reduces path length by 9.8% compared to the artificial potential field method and improves trajectory smoothness by 22.7%. It also increases the minimum obstacle clearance distance by 45.3% compared to the RRT algorithm, achieving a favorable balance between path efficiency and flight safety.