A Perception‐Aware Hierarchical Planning Framework for Multi‐Target Substation Inspection With UAVs

ABSTRACT Unmanned aerial vehicles (UAVs) are becoming widely used for electrical substation inspection, which is essential to ensure the reliability and stability of power systems. In recent years, UAV‐based inspection techniques and perception‐aware trajectory planning algorithms have been developed. However, most existing studies do not consider the spatial organization of substations and instead rely on fixed, single trajectories, thereby limiting the ability to perform inspections in a rational and efficient manner. Moreover, they do not provide a comprehensive analysis of multi‐objective observation under limited field‐of‐view (FOV) constraints, resulting in insufficient coverage of the inspection targets. To address these issues, we propose a perception‐aware planning framework for multi‐target inspection. First, we present a hierarchical planning framework, ensuring structured and efficient inspection of the substation. Then a perception‐aware planner for multi‐objective observation is proposed to provide efficient and feasible trajectories while ensuring maximum visibility of the targets. Finally, both simulation and real‐world experiments in comparison with state‐of‐the‐art algorithms are conducted to validate the superiority of the proposed method, which achieves an FOV coverage rate that is – higher than those of the baseline algorithms.