Task Parameter Planning Algorithm for UAV Area Complete Coverage in EO Sector Scanning Mode

When Unmanned Aerial Vehicles (UAVs) are used in search and rescue operations, electro-optical (EO) devices usually as the detection equipment, area coverage is main method. However, sector scanning mode of EO puts forward higher requirements for task parameter planning. First, to ensure there no missing coverage, a method determine full width equipment proposed. Second, constraint interval model speed-to-high ratio established, constraints other factors addressed context problem situation. Third, efficiency index proposed boustrophedon rectangular area, comprehensive established. Finally, planning algorithms designed, based on Immune Algorithm (IA), Grey Wolf Optimization (GWO) Variable Neighborhood Search (VNS), respectively. The simulation results showed that designed algorithms, IA, GWO VNS, can effectively solve problems. In general, IA more suitable offline occasions, VNS online real-time planning, has characteristics between two. process, optimized parameters, meets all constraints, does not miss areas, proving correctness these models effectiveness algorithm. research presented this paper provides technical basis efficient fully automated target rescue.