Distributed UAV swarm control framework with limited interaction for obstacle avoidance

被引:5
作者
Zhu, Baitao [1 ]
Deng, Yimin [1 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Distributed swarm control; Neighbor selection; Informed UAV; Limited interaction; Obstacle avoidance; SYSTEM;
D O I
10.1108/AEAT-04-2022-0099
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
PurposeThe purpose of this paper is to propose a distributed unmanned aerial vehicle (UAV) swarm control method to ensure safety and obstacle avoidance during swarm flight and realize effective guidance. Design/methodology/approachThis paper proposes a distributed UAV swarm control framework with limited interaction. UAVs in the swarm realize the selection of limited interactive neighbors according to the random line of sight and limited field of view. The designed interaction force and obstacle avoidance mechanism are combined to ensure the safety of UAVs and avoid collisions and obstacles. Informed UAVs are deployed to guide the swarm to move in the desired direction. FindingsThe proposed distributed swarm control framework achieves high safety of swarm motion and the participation of informed UAVs is conducive to the guidance of the UAV swarm. Simulation results demonstrate the feasibility and effectiveness of the proposed approach. Practical implicationsThe UAV swarm control method developed in this paper can be applied to the practice of UAV swarm control. Originality/valueA distributed UAV swarm control method is proposed to ensure the effective control of the consistency and safety of swarm motion.
引用
收藏
页码:697 / 705
页数:9
相关论文
共 25 条
[1]  
Beard R.W., 2012, Small Unmanned Aircraft: Theory and Practice
[2]   Implicit coordination for 3D underwater collective behaviors in a fish-inspired robot swarm [J].
Berlinger, Florian ;
Gauci, Melvin ;
Nagpal, Radhika .
SCIENCE ROBOTICS, 2021, 6 (50)
[3]   Effective leadership and decision-making in animal groups on the move [J].
Couzin, ID ;
Krause, J ;
Franks, NR ;
Levin, SA .
NATURE, 2005, 433 (7025) :513-516
[4]   Collective memory and spatial sorting in animal groups [J].
Couzin, ID ;
Krause, J ;
James, R ;
Ruxton, GD ;
Franks, NR .
JOURNAL OF THEORETICAL BIOLOGY, 2002, 218 (01) :1-11
[5]   Collective detection based on visual information in animal groups [J].
Davidson, Jacob D. ;
Sosna, Matthew M. G. ;
Twomey, Colin R. ;
Sridhar, Vivek H. ;
Leblanc, Simon P. ;
Couzin, Iain D. .
JOURNAL OF THE ROYAL SOCIETY INTERFACE, 2021, 18 (180)
[6]   Relevance of Metric-Free Interactions in Flocking Phenomena [J].
Ginelli, Francesco ;
Chate, Hugues .
PHYSICAL REVIEW LETTERS, 2010, 105 (16)
[7]   A Time Optimal Reactive Collision Avoidance Method for UAVs Based on a Modified Collision Cone Approach [J].
Gnanasekera, Manaram ;
Katupitiya, Jay .
2020 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2020, :5685-5692
[8]   Modelling hierarchical flocking [J].
Jia, Yongnan ;
Vicsek, Tamas .
NEW JOURNAL OF PHYSICS, 2019, 21
[9]   Energy-Efficient Ground Traversability Mapping Based on UAV-UGV Collaborative System [J].
Li, Jianqiang ;
Cheng, Yanyan ;
Zhou, Jin ;
Chen, Jie ;
Liu, Zun ;
Hu, Shuqing ;
Leung, Victor C. M. .
IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING, 2022, 6 (01) :69-78
[10]   Bio-inspired self-organized cooperative control consensus for crowded UUV swarm based on adaptive dynamic interaction topology [J].
Liang, Hongtao ;
Fu, Yanfang ;
Gao, Jie .
APPLIED INTELLIGENCE, 2021, 51 (07) :4664-4681