城市环境下的异构多无人机层次化任务分配

Hierarchical task allocation for heterogeneous multi-UAV in an urban terrain

针对多无人机应用于城市环境问题,设计了一种MUAV与SUAV层次化任务分配方案,并分析了MUAV对SUAV执行目标任务成功率的影响,将影响因子加入目标函数,提出了一种无人机探测范围内的层次化任务分配模型.采用连续粒子群(PSO)算法对问题进行求解,通过加入惯性权重的凹函数递减策略与将人工蜂群(ABC)算法引入到粒子群迭代环节,较好地解决粒子群算法易陷入局部最优的问题,同时提高算法收敛速度.仿真结果表明所提出的模型可以较好地解决城市环境下的多无人机层次化任务分配问题.

A hierarchical task allocation of MUAV and SUAV was proposed to solve the problem of multi-UAV application in an urban terrain.The influence factor on task success rate of SUAV was an-alysed,which was also added to the objective function to build the task allocation model inside the de-tection range.The particle swarm optimization (PSO)algorithm for solving the problem was presen-ted,based on the strategy that the inertia weight declined with the concave function.Search operator of artificial bee colony was also introduced into the algorithm to solve the problems of premature con-vergence frequently appeared in standard PSO algorithm and its poor convergence.The simulation re-sults show that the model and the algorithm can effectively solve the hierarchical task allocation for heterogeneous multi-UAV in an urban terrain.