Abstract—

Parallel and pipeline methods for performing complex flight missions by groups of intelligent unmanned aerial vehicles (UAVs) are comparatively analyzed to find the most effective way for performing such missions under the criteria of minimum time and limited functionality of onboard computers. A model of knowledge representation for planning goal-oriented behavior in the a priori undescribed problem environment regardless of the specific domain is proposed. Procedures for knowledge processing and inference on semantic networks are developed for planning goal-oriented behavior of intelligent UAVs in the process of performing various subtasks of a complex flight mission with polynomial complexity.

中文翻译：

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为智能无人机组计划复杂的飞行任务

摘要-

对通过智能无人飞行器（UAV）组执行复杂飞行任务的并行和流水线方法进行了比较分析，以在最短时间和机载计算机功能受限的条件下找到执行此类任务的最有效方法。提出了一种知识表示模型，用于在先验未描述的问题环境中规划面向目标的行为，而与特定领域无关。开发了知识处理和语义网络推理程序，以在执行具有多项式复杂性的复杂飞行任务的各种子任务的过程中，规划智能无人机的面向目标的行为。