基于改进社区发现算法的多智能体覆盖控制

Hongyan Li, Shengjin Li, Zhen Wang, Chong Li, Shan Gao, Dengxiu Yu
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引用次数: 0

摘要

本文提出了一种基于社区发现算法的覆盖控制方法。在传统的覆盖控制中,采用Voronoi划分方法对目标区域进行划分。然而,它不能应用于平面的凹区或高维空间。因此,我们提出了一种基于社区发现算法的覆盖控制方法,该方法可以应用于离散、凹和高维区域。此外,我们还引入了Delaunay三角剖分的方法来生成不同agent之间的拓扑关系。从而解决了一组具有内连接点的覆盖控制问题。通过两个算例仿真验证了该方法的有效性。
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Multi-agent coverage control based on improved community discovery algorithm
In this paper, we propose a coverage control method based on the community discovery algorithm. In the traditional coverage control, the Voronoi partition method is used to divide the target region. However, it cannot be applied in the concave area of the plane or the high-dimensional space. Hence, we propose a coverage control method based on the community discovery algorithm, which can be applied in discrete, concave, and high-dimensional areas. In addition, we introduce the method of Delaunay triangulation to generate the topological relationship between different agents. As a result, the coverage control method of a set of points with internal connections is solved. And the coverage control method is proved to be effective by two examples in simulation.
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