无人机集群实时任务分配方法研究

Study on Task Allocation of UAV Swarm Based on Cognitive Control

针对无人机(Unmanned Aerial Vehicle, UAV)集群实时任务分配,提出了一种集中式分配方法。该方法基于实时战场态势,依靠协调调度层进行分配决策,依据打击效费比生成打击顺序,针对战场实时态势滚动优化,使分配结果能够在当前认知范围内始终保持优化和效率的平衡。针对粒子群算法求解任务分配,设计了一种粒子二维0-1编码方法和一种针对不规范粒子的修正方法。仿真结果表明,设计的粒子群算法能够快速收敛,所提方法能够有效解决有实时要求的任务分配。

A centralized allocation method for Unmanned Aerial Vehicle(UAV) swarm real-time task allocation is proposed. Based on the real-time battlefield situation, this method relies on the coordination scheduling layer to make allocation decisions, generates the strike order according to the strike efficiency ratio, and makes rolling optimization for real-time battlefield situation, so that the allocation results can always maintain the balance between optimization and efficiency within the current cognitive range. Particle swarm optimization(PSO) is used to solve the task assignment problem. In particular, a 2-D particle 0-1 coding and correction method for nonstandard particles is designed. The simulation results show that the proposed PSO algorithm can converge quickly and the proposed method can effectively solve the task assignment problem with real-time requirements.