基于稳定匹配的异质无人机集群“分布式”协同算法研究
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国防科技大学系统工程学院

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TP273

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国家自然科学基金项目(面上项目,重点项目,重大项目)


Research on Autonomous Collaborative Algorithm of Heterogeneous UAV Swarm Based on Stable Matching
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National University of Defense Technology,Colledge of Systems Engineering

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    摘要:

    无人机集群凭借其成本低、态势感知能力强、可协同执行任务等特点得到飞速发展,针对无人机集群自主协同的研究也受到世界各国的广泛关注。本文针对同质无人机集群功能单一而无法执行复杂任务的缺陷,重点研究面向异质无人机集群的“分布式”协同作战问题,首先,对异质无人机“分布式”协同作战方式进行描述;然后设计了基于异质无人机能力的协同度计算模型;接着基于稳定匹配思想,以最大化全局协同度为目标,提出了异质无人机“分布式”协同作战的线性优化模型,并给出了对匹配方案协同效果的评价方法。最后通过三组实验,验证了本文所提出的模型与方法的有效性,相较于基准算法具有更高的运算效率和效果,同时在大规模算例中也有良好的匹配效果。

    Abstract:

    Due to its low cost, strong situational awareness and ability to perform tasks cooperatively, etc, unmanned aerial vehicle (UAV) technology is developing rapidly, and the research on autonomous coordination of UAV swarm has been widely concerned and studied all over the world. This paper focuses on the problem of "distributed" cooperative operation oriented to heterogeneous UAV swarm, aiming at the defect that homogeneous UAVs have a single function and cannot perform complex tasks. Firstly, the "distributed" cooperative operation mode of heterogeneous UAV swarm is described. Then, a collaborative computing model based on heterogeneous UAV capability is designed.Then, based on the idea of stable matching and aiming at maximizing the global synergy, a linear optimization model of heterogeneous UAV swarm "distributed" synergy degree was proposed, and the evaluation methods for the synergetic effect of matching scheme was given. Finally, through three groups of experiments, the effectiveness of the model and method proposed in this paper is verified. Compared with the benchmark algorithm, it has higher operational efficiency and effect, and also has good matching effect in large-scale examples.

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历史
  • 收稿日期:2020-09-14
  • 最后修改日期:2021-02-04
  • 录用日期:2021-02-10
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