Journal of Bionic Engineering ›› 2023, Vol. 20 ›› Issue (2): 782-796.doi: 10.1007/s42235-022-00287-w

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Distributed Flocking Algorithm for Multi-UAV System Based on Behavior Method and Topological Communication

Yifei Feng1; Jingshi Dong1; Jianlin Wang2; Hang Zhu1   

  1. 1 Key Laboratory of CNC Equipment Reliability, Ministry of Education, School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China  2 Department of Mechanical Engineering, The University of Melbourne, Melbourne, VIC 3052, Australia
  • 出版日期:2023-03-10 发布日期:2023-03-15
  • 通讯作者: Hang Zhu E-mail:hangzhu@jlu.edu.cn
  • 作者简介:Yifei Feng1; Jingshi Dong1; Jianlin Wang2; Hang Zhu1

Distributed Flocking Algorithm for Multi-UAV System Based on Behavior Method and Topological Communication

Yifei Feng1; Jingshi Dong1; Jianlin Wang2; Hang Zhu1   

  1. 1 Key Laboratory of CNC Equipment Reliability, Ministry of Education, School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China  2 Department of Mechanical Engineering, The University of Melbourne, Melbourne, VIC 3052, Australia
  • Online:2023-03-10 Published:2023-03-15
  • Contact: Hang Zhu E-mail:hangzhu@jlu.edu.cn
  • About author:Yifei Feng1; Jingshi Dong1; Jianlin Wang2; Hang Zhu1

摘要: There are many interesting flocking phenomena in nature, such as joint predation and group migration, and the intrinsic communication patterns of flocking are essential for studying group behavior. Traditional models of communication such as the pigeon flock model and the wolf pack model define all agents within a perceptual distance as the neighborhoods, and some models have fixed communicating numbers. There is a significant impact on the quality of the flocking formation when encountering poor initial state of the flocking, multiple obstacles, or loss of certain agents. To solve this problem, this paper proposes a local communication model with nearest agents in four directions. Based on this model and behavioral method, two distributed flocking formation algorithms are designed in this paper for different scenarios, namely the flocking algorithm and the circular formation algorithm. Numerical simulation results show that the flocking can pass through the obstacle area and re-formation smoothly, and also the formation quality of the flocking is better compared with the traditional communication model.

关键词: Multi-UAV system , · Distributed control , · Flocking formation , · Topological communication , · Bioinspired

Abstract: There are many interesting flocking phenomena in nature, such as joint predation and group migration, and the intrinsic communication patterns of flocking are essential for studying group behavior. Traditional models of communication such as the pigeon flock model and the wolf pack model define all agents within a perceptual distance as the neighborhoods, and some models have fixed communicating numbers. There is a significant impact on the quality of the flocking formation when encountering poor initial state of the flocking, multiple obstacles, or loss of certain agents. To solve this problem, this paper proposes a local communication model with nearest agents in four directions. Based on this model and behavioral method, two distributed flocking formation algorithms are designed in this paper for different scenarios, namely the flocking algorithm and the circular formation algorithm. Numerical simulation results show that the flocking can pass through the obstacle area and re-formation smoothly, and also the formation quality of the flocking is better compared with the traditional communication model.

Key words: Multi-UAV system , · Distributed control , · Flocking formation , · Topological communication , · Bioinspired