基于SEAD任务特性约束的协同任务分配方法

Research on cooperative task assignment method used to the mission SEAD with real constraints

以多异构无人机执行SEAD任务为背景,开展协同任务分配问题建模、算法设计和仿真分析.采用图论的方法完成问题的建模,将无人机本体等效为Dubins Car模型,并对其在相应目标处执行侦查、打击、评估任务时的进入角度进行约束,通过Dubins路径完成对无人机飞行路径的等效,采用分布式遗传算法完成对问题的快速求解.研究结果表明,带有路径末端角度约束的任务分配问题具有较好的实用意义,分布式遗传算法可有效处理实时任务分配问题,完成任务空间的快速决策.

In the background of heterogeneous UAVs performing suppression of enemy air defences（SEAD） mission, this paper establishes the models for the cooperative task assignment problem, designs the solving algorithm, and carries out the simulation analysis. Firstly, the paper employs the graph theory to transform the problem to a directed graph, and uses the Dubins Car model to stand for the UAV＇s kinematic model. Then, the paper takes the constraints of the subtask including searching, verifing and attacking. Furthermore, the paper adopts a distributed framework to the genetic algorithm in order to improve the operation efficiency of the algorithm. Finally, simulation results show the practicability of the proposed algorithm.