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An Adaptive Sequential Game Theoretic Approach to Coordinated Mission Planning for Aerial Platforms

机译：空中平台协同任务规划的自适应序贯博弈论方法

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Coordinated mission planning is one of the core steps to effectively exploit the capabilities of cooperative control of multiple UAVs. In this chapter, we extend and implement an effective team composition and tasking mechanism and an optimal team dynamics and tactics algorithm for mission planning under a hierarchical adaptive sequential game theoretic framework. Our knowledge/experience based static non-cooperative and non-zero games are used for team composition and tasking to schedule tasks at the mission level and allocate resources associated with these tasks. The dynamic adaptive sequential game model is used for team dynamics and tactics to assign targets and decide the optimal salvo size for each aerial platform to achieve the minimum remaining platforms of red and the maximum remaining platforms of blue at the end of a battle. A simulation software package has been developed to demonstrate the performance of our proposed algorithms.
机译：任务协调计划是有效利用多种无人机协同控制能力的核心步骤之一。在本章中，我们扩展并实现了一种有效的团队组成和任务分配机制，以及在分层自适应序贯博弈理论框架下用于任务计划的最佳团队动力学和战术算法。我们基于知识/经验的静态非合作和非零游戏用于团队组成和任务分配，以在任务级别安排任务并分配与这些任务相关的资源。动态自适应顺序博弈模型用于团队动力和战术，以分配目标并确定每个空中平台的最佳齐射尺寸，以在战斗结束时实现红色的最小剩余平台和蓝色的最大剩余平台。开发了一个模拟软件包来演示我们提出的算法的性能。

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