Autonomous Mission Planning Method For Multiple Unmanned Aerial Vehicles

In the future, multiple unmanned aerial vehicles(UAVs) cooperative combat is an important development trend. Besides, the mission planning in especial the cooperative mission planning for multi-UAV under complex environment as one of the key technologies in autonomous control is of great significance in enhancing the survivability and task completion rate. In this paper, autonomous cooperative search and reconnaissance-attack mission planning algorithms for multi-UAV system are studied. The model predictive control(MPC) theory is utilized in this paper. The ant colony optimization(ACO) and particle swarm optimization(PSO) algorithm are used as the mainly optimization tools and some advancements are made to improve the performance of the original algorithm. Meanwhile, the comparison simulations are carried out.Firstly, the cooperative searching mission planning algorithm for multiple isomorphic reconnaissance UAVs is designed. The global mission planning optimization model is established based on the environment model and the goal model and then decomposed into some local optimization problems under the structure of distributed model predictive control(DMPC). The local optimization problem is solved by PSO algorithm. The advantages of the designed distributed algorithm in time consumption and target reconnaissance are verified by comparing with the centralized searching algorithm and other diatributed searching algorithms.Secondly, the cooperative reconnaissance-attack mission planning algorithm for multiple isomorphic reconnaissance-attack integration UAVs is studied. An improved distributed ACO algorithm is proposed to solve the reconnaissance-attack mission planning problem under the adversarial environment. The convergence and adaptivity performance of the proposed algorithm are verified by a series of simulations.Finally, a cooperative reconnaissance-attack mission planning algorithm for a specific kind of heterogeneous multi-UAV system which consists of reconnaissance UAVs and reconnaissance-attack integration UAVs is proposed. The heterogeneous system is decomposed into two isomorphic systems, which are isomorphic reconnaissance UAVs and isomorphic reconnaissance-attack integration UAVs. Then a novel cooperative mode is designed at the basis of searching and reconnaissance-attack mission planning algorithms to realize the reconnaissance-attack mission planning for heterogeneous system. Meanwhile, the effectiveness of the proposed algorithm is verified by simulations.