Optimized Multi-Unmanned Aerial Vehicle Coverage Path Planning for Efficient Solar Panel Cleaning: A Rectilinear and Vehicle Routing Problem-Based Approach

Abstract

Abstract. This study proposes a novel methodology for efficient multi-unmanned aerial vehicle (UAV) coverage path planning (CPP) tailored to solar panel cleaning applications. The approach incorporates rectilinear path planning and vehicle routing problem (VRP) strategies, enabling optimized and coordinated multi-UAV operations for large-scale solar farms. By systematically dividing the target area into rows and assigning optimized routes to UAVs, the methodology minimizes mission time and maximizes cleaning efficiency. The proposed CPP approach integrates realistic constraints such as UAV battery life, flight time, and operator limitations, ensuring practicality and robustness. Comprehensive evaluations, including simulations using the Gazebo platform and real-world tests with UAVs, validate the effectiveness of the methodology. The results demonstrate significant improvements in path optimization, energy efficiency, and area coverage, confirming its applicability to solar panel maintenance and other large-scale coverage tasks.