For multiple unmanned aerial vehicles (UAVs) performing aerial search-attack tasks, there is a tradeoff between maximizing total benefit and minimizing consumption under the validity of constraints. This article proposes a dynamic discrete pigeon-inspired optimization algorithm to handle cooperative search-attack mission planning for UAVs, which integrates the centralized task assignment and distributed path generation aspects of the problem. Besides, a solution acceptance strategy is proposed to avoid frequent task switching. To design a reasonable objective function, the probability map is constructed and updated by Bayes formula to guide the following search motion, and a response threshold sigmoid model is adopted for target allocation during executing attack. Moreover, the flyable trajectories are generated by B-spline curves based on the simplified waypoints. Finally, numerical experiments prove that the proposed methods can provide feasible solutions for multiple UAVs considering different scenarios, such as the absence or presence of threats and insufficient resources. The results also show that the solution acceptance strategy is effective to improve performance. Moreover, the extensible mission planning system also integrates with an interactive 3D visualization simulation module, where the multi-UAV coordinated flight processes are demonstrated dynamically.

中文翻译：

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动态离散鸽子启发的多无人机协同搜索-攻击任务计划优化

对于执行空中搜索攻击任务的多架无人飞行器（UAV），在约束的有效性下，要在最大化总收益和最小化消耗之间进行权衡。本文提出了一种动态离散鸽子启发式优化算法来处理无人机的协同搜索-攻击任务计划，该算法将问题的集中式任务分配和分布式路径生成集成了起来。此外，提出了一种解决方案接受策略，以避免频繁的任务切换。为了设计合理的目标函数，利用贝叶斯公式构造并更新了概率图，以指导后续的搜索动作，并在执行攻击过程中采用响应阈值S形模型进行目标分配。而且，B样条曲线基于简化的航路点生成可飞行轨迹。最后，数值实验证明，所提出的方法可以为考虑到不同情况（例如威胁的存在与否以及资源不足）的多种无人机提供可行的解决方案。结果还表明，解决方案接受策略可有效提高性能。此外，可扩展的任务计划系统还与交互式3D可视化仿真模块集成，可以动态演示多无人机协同飞行过程。结果还表明，解决方案接受策略可有效提高性能。此外，可扩展的任务计划系统还与交互式3D可视化仿真模块集成，可以动态演示多无人机协同飞行过程。结果还表明，解决方案接受策略可有效提高性能。此外，可扩展的任务计划系统还与交互式3D可视化仿真模块集成，可以动态演示多无人机协同飞行过程。