VBCA：一种用于自主空中无人机系统的虚拟力聚类算法
VBCA: A Virtual Forces Clustering Algorithm for Autonomous Aerial Drone Systems
AI总结：
本文提出VBCA算法，利用虚拟力实现无人机自主定位，形成高效三维拓扑结构，提升覆盖效率和网络连通性。
摘要：
本文提出VBCA算法，利用虚拟力实现无人机自主定位，形成高效三维拓扑结构，提升覆盖效率和网络连通性。
英文摘要：
We consider the positioning problem of aerial drone systems for efficient three-dimensional (3-D) coverage. Our solution draws from molecular geometry, where forces among electron pairs surrounding a central atom arrange their positions. In this paper, we propose a 3-D clustering algorithm for autonomous positioning (VBCA) of aerial drone networks based on virtual forces. These virtual forces induce interactions among drones and structure the system topology. The advantages of our approach are that (1) virtual forces enable drones to self-organize the positioning process and (2) VBCA can be implemented entirely localized. Extensive simulations show that our virtual forces clustering approach produces scalable 3-D topologies exhibiting near-optimal volume coverage. VBCA triggers efficient topology rearrangement for an altering number of nodes, while providing network connectivity to the central drone. We also draw a comparison of volume coverage achieved by VBCA against existing approaches and find VBCA up to 40\% more efficient.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
