无人机巡检优化建模方法综述OA

Low-altitude inspection technology is evolving into a key component of modern inspection systems due to its significant advantages in cost reduction and efficiency improvement.The efficient operation of unmanned aerial vehicle(UAV)inspections relies on a well-structured top-level planning system,whose core challenges can be summarized into three closely related decision-making layers:site selection,task allocation,and path planning.This paper systematically reviews the current research status and modeling methodologies of this integrated plan-ning framework.Firstly,task characteristics are classified and analyzed from multiple dimensions,including inspec-tion targets,operational scenarios,and task combinations.Subsequently,the modeling approaches,optimization ob-jectives,and constraint systems of the three core layers—site selection,task allocation,and path planning—are elaborated in detail.By establishing a three-tier analytical framework,the review provides a more systematic and hi-erarchical analytical perspective for the field.Finally,addressing current research bottlenecks in system coordina-tion,real-time responsiveness,and environmental adaptability,future research directions are outlined.These in-clude three-level integrated optimization,cloud-edge-device collaborative computing,and robust planning through the integration of data-driven and physics-based models.The goal of this study is to offer a comprehensive refe-rence for both theoretical research and engineering practice in the advancement of intelligent planning systems for UAV inspection.