Real-Time Path Planning for Power Tower Inspection Based on Hybrid Algorithm

The sequence of conventional shooting viewpoints for power tower is fixed and the inspection distance of multi-rotor UAV is not optimal. In addition, as the dimension increases, the path planning algorithm cannot meet the requirements of real-time path planning because the space complexity increases exponentially. Aiming at those problems, a three-dimensional path planning method for power tower inspection is proposed based on ant colony optimization and A * (ACO-A*) hybrid algorithm. The method is composed of global planning and local planning. Firstly, the global planning uses the ant colony optimization algorithm to find a relatively optimal path that covers all viewpoints, and to judge whether the path passes through obstacles. And then the A* algorithm is used for local planning. The simulation results show that the path length planned by the proposed ACO-A* algorithm is reduced by 16.68% compared to that stipulated in the Shooting Manual for UAV Inspection Images of Overhead Transmission Lines, and the path planning time is reduced by 99.68% compared to that of the A* algorithm. Therefore, the proposed method not only reduces the energy consumption for inspection, but also enhances the efficiency of path planning.