arXiv 2405.112812024-05-18cs.DCcs.AI

无人机集群中的协作认知动态系统：可重构机制与框架

Cooperative Cognitive Dynamic System in UAV Swarms: Reconfigurable Mechanism and Framework

College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics（南京航空航天大学电子信息工程学院）；State Key Laboratory of ISN, Xidian University（西安电子科技大学ISN国家重点实验室）；School of Computer Science and Engineering, Nanyang Technological University（南洋理工大学计算机科学与工程学院）；University of Houston（休斯顿大学）；Department of Computer Science and Engineering, Kyung Hee University（庆熙大学计算机科学与工程系）

Ziye Jia, Jiahao You, Chao Dong, Qihui Wu, Fuhui Zhou, Dusit Niyato, Zhu Han

阅读 PDF

arXiv 页面 ↗HTML 原文 ↗

AI总结：

针对无人机集群实时适应性管理不足的问题，提出CCDS分层协作框架，通过动态重构、自适应优化、仿生任务分配与分布式协调提升鲁棒性。

摘要：

随着民用和军事领域对即时有效响应需求的不断增长，无人机（UAV）集群成为有效的解决方案，其中多架协作式无人机能够协同工作以实现特定目标。然而，如何管理此类复杂系统以确保实时适应性，仍缺乏充分研究。因此，本文提出协作认知动态系统（CCDS），以优化无人机集群管理。CCDS采用分层协作控制结构，支持实时数据处理与决策。相应地，CCDS通过动态可重构性和自适应智能优化来优化无人机集群管理。此外，CCDS可与仿生机制集成，从而高效地为无人机集群分配任务。进一步而言，CCDS的分布式协调可确保可靠且具弹性的控制，从而增强适应性和鲁棒性。最后，本文分析了潜在挑战与未来方向，以为在动态异构组网中管理无人机集群提供洞见。

英文摘要：

As the demands for immediate and effective responses increase in both civilian and military domains, the unmanned aerial vehicle (UAV) swarms emerge as effective solutions, in which multiple cooperative UAVs can work together to achieve specific goals. However, how to manage such complex systems to ensure real-time adaptability lack sufficient researches. Hence, in this paper, we propose the cooperative cognitive dynamic system (CCDS), to optimize the management for UAV swarms. CCDS leverages a hierarchical and cooperative control structure that enables real-time data processing and decision. Accordingly, CCDS optimizes the UAV swarm management via dynamic reconfigurability and adaptive intelligent optimization. In addition, CCDS can be integrated with the biomimetic mechanism to efficiently allocate tasks for UAV swarms. Further, the distributed coordination of CCDS ensures reliable and resilient control, thus enhancing the adaptability and robustness. Finally, the potential challenges and future directions are analyzed, to provide insights into managing UAV swarms in dynamic heterogeneous networking.

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。