Anti-collision control of UAVs based on swarm intelligence mechanism

  • JIANG Longting ,
  • WEI Ruixuan ,
  • ZHANG Qirui ,
  • WANG Dong
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  • 1. Graduate College, Air Force Engineering University, Xi'an 710038, China;
    2. Aeronautics Engineering College, Air Force Engineering University, Xi'an 710038, China;
    3. Troop 95561 of PLA, Rikaze 857000, China

Received date: 2020-05-26

  Revised date: 2020-06-01

  Online published: 2020-06-24

Supported by

Key Projects of the Ministry of Science and Technology of "New Generation Artifical Intelligence"(2018AAA0102403);National Natural Science Foundation of China (61573373)

Abstract

UAV clusters with high reliability and an efficient cost ratio have attracted extensive attention in both combat missions and civil use. The opening of urban low-altitude airspace and the dramatically increasing dynamic complexity of combat environments impose severe challenges for UAV cluster collision prevention. To solve the problem of collision prevention in both formation and encountering with sudden obstacles, a cluster collision prevention control method based on the swarm intelligence mechanism is proposed. The models of attraction, repulsive force and formation configuration force within the cluster are designed by introducing the concept of mechanics, and a collision prevention model of UAVs based on group information sharing and brain-like knowledge development is constructed through information sharing among individuals in the cluster and the development of brain-like knowledge. The simulation results show that the proposed cluster control method can improve the clustering efficiency, avoid suddenly encountered dynamic obstacles, and complete formation reconstruction. The introduction of swarm intelligence mechanism can shorten the response time of UAV clusters in face of sudden obstacles.

Cite this article

JIANG Longting , WEI Ruixuan , ZHANG Qirui , WANG Dong . Anti-collision control of UAVs based on swarm intelligence mechanism[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020 , 41(S2) : 724294 -724294 . DOI: 10.7527/S1000-6893.2020.24294

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