多无人机协同机场驱鸟任务分配

为解决传统机场驱鸟效率不高的问题，将多无人机协同技术引入该领域，基于自创的“伏击法”的驱鸟策略完成任务规划建模，并设计了一种基于遗传算法的任务分配方法。分别引入了推理树分析法和模糊逻辑分析法对参数进行优化选择，评价鸟击威胁和无人机拦截效率这两个任务规划的前置条件。设计了多个约束条件以保证任务规划的实际效果，并基于比例导引制导律对无人机执行任务时间进行估计。仿真实例表明，该方法在多个约束条件和同时面临多个鸟类目标的条件下，能有效完成多无人机协同驱鸟任务分配工作。

Cooperative Task Assignment of Multi-UAVs Bird-Driving at Airport

In order to solve the problem of inefficiency of traditional bird-driving methods at the Airport，this paper introduces the technology of multi-UAVs cooperation into this field． We study a bird-driving technology by using multi-UAVs cooperative． Based on the self-created“bird-ambushed”strategy，a mission planning model is built and a task assignment method is designed based on genetic algorithm． In order to evaluate the parameters of bird strike threat，the UAV interception efficiency which are the preconditions of the mission planning． The reasoning tree analysis and fuzzy logic analysis were introduced to optimize the parameters，respectively． In order to ensure the actual effect of mission planning，multiple constraints are designed，and the mission time of UAV is estimated based on proportional guidance law． The numerical simulation results show that，under the condition of multiple constraints and multiple bird targets simultaneously，the developed method can effectively accomplish the work of multi-UAVs cooperative bird-driving．