UAV Swarm Intelligence: Recent Advances and Future Trends

被引:146
作者
Zhou, Yongkun [1 ]
Rao, Bin [1 ]
Wang, Wei [1 ]
机构
[1] Sun Yat Sen Univ, Sch Elect & Commun Engn, Guangzhou 510006, Peoples R China
关键词
Task analysis; Planning; Particle swarm optimization; Drones; Heuristic algorithms; Clustering algorithms; UAV; swarm intelligence; hierarchical control framework; trend; COLLISION-AVOIDANCE; CIVIL APPLICATIONS; CELLULAR NETWORKS; FLOCKING CONTROL; TASK-ASSIGNMENT; SYSTEM; VEHICLES; SEARCH; COMMUNICATION; OPTIMIZATION;
D O I
10.1109/ACCESS.2020.3028865
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The dynamic uncertain environment and complex tasks determine that the unmanned aerial vehicle (UAV) system is bound to develop towards clustering, autonomy, and intelligence. In this article, we present a comprehensive survey of UAV swarm intelligence from the hierarchical framework perspective. Firstly, we review the basics and advances of UAV swarm intelligent technology. Then we look inside to investigate the research work by classifying UAV swarm intelligence research into five layers, i.e., decision-making layer, path planning layer, control layer, communication layer, and application layer. Furthermore, the relationship between each level is explicitly illustrated, and the research trends of each layer are given. Finally, limitations and possible technology trends of swarm intelligence are also covered to enable further research interests. Through this in-depth literature review, we intend to provide novel insights into the latest technologies in UAV swarm intelligence.
引用
收藏
页码:183856 / 183878
页数:23
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