Cooperative Mission Planning for Heterogeneous UAVs with the Improved Multi-objective Quantum-behaved Particle Swarm Optimization Algorithm

摘要: The cooperative operation of the unmanned aerial vehicle (UAV) is trend application UAVs. Mission planning basis UAV formation. appropriate mission can fully utilize technical potential and increase effectiveness. should consider several criteria, like completion time, expected benefit, energy consumption or equipment loss. Hence, it be treated as a Multi-objective Optimization Problem. Aiming to characteristics heterogeneous formation in anti-radar operations, model based on multi-objective optimization proposed. collaborative constraint between UAVs execution established through multi-layer coding penalty function. solved by an improved Quantum-Behaved Particle Swarm Optimization. crossover mutation Genetic Algorithm are introduced enhance diversity solutions. Finally, proposed algorithm verified simulation experiments.