Energy-Efficient UAV Trajectory Planning for Wind Turbine Inspection

The core task of unmanned aerial vehicle (UAV) inspection for wind turbines lies in path planning, with the primary objectives being comprehensive coverage of the turbines and improved energy efficiency. Existing methods are mostly applicable to facilities with simple structures, overlooking the complex characteristics of wind turbines and failing to adequately consider energy consumption issues. To address this, this paper proposes a UAV inspection path planning method that balances turbine coverage and energy consumption, aiming to enhance the efficiency of wind turbine surface inspection. First, the method designs a two-step “sampling-optimization” viewpoint sampling strategy tailored to the structural features of wind turbines, planning viewpoints for both the blade hub and tower sections. For the blade hub section, each triangular surface is sampled first, followed by viewpoint optimization using a greedy algorithm to reduce redundant viewpoints while ensuring coverage. For the tower section, a spiral ascent sampling approach is adopted to reduce energy consumption and improve efficiency. Second, by analyzing path energy consumption factors, the method combines the LKH algorithm with an improved Optimal Rapidly-Exploring Random Tree (RRT*) algorithm to optimize path planning and minimize drone turns during navigation. Finally, an energy-efficient trajectory planning strategy is proposed based on UAV energy consumption models. By restricting flight speed within the energy-efficient optimal range and employing a minimum snap trajectory generation method to smooth trajectories, unnecessary acceleration and deceleration are minimized, effectively reducing energy consumption. Simulation results show that the proposed method produces shorter and smoother inspection trajectories, leading to reduced total energy consumption under identical speed constraints.