APF-APSO: UAV Swarm Cooperation Algorithm for Multi-target Search in Complex Reconnaissance Environments

Zhi Li*, Xinting Zhang, Lei Lei, Lijuan Zhang, Xiaoqin Song

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Multi-target search is a key part of UAV swarm cooperative reconnaissance. UAVs need to avoid threats in complex reconnaissance environments. In this paper, an optimization algorithm combining the artificial potential field with adaptive particle swarm algorithm (APF-APSO) is proposed for UAV swarm cooperative multi-target search mission. Firstly, we combine the PSO algorithm with the APF algorithm, adding a repulsive force field generated by the UAV's search path and using the force field function as a fitness function, which improves the obstacle avoidance and search efficiency of the UAV swarm. Secondly, a method for self-adaptive adjustment of personal cognition and social cognition factors is proposed, and an adaptive adjustment strategy of inertia weight is introduced to avoid the search falling into local optimum. The simulation results show that the proposed algorithm has higher search efficiency compared with other two PSO baseline algorithms in the same situation.

Original languageEnglish
Title of host publication2022 Workshop on Electronics Communication Engineering
EditorsLetian Huang
PublisherSPIE
ISBN (Electronic)9781510666634
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event2022 Workshop on Electronics Communication Engineering - Xi'an, China
Duration: 28 Oct 202231 Oct 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12720
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2022 Workshop on Electronics Communication Engineering
Country/TerritoryChina
CityXi'an
Period28/10/2231/10/22

Keywords

  • APF
  • Multi-target search
  • PSO
  • UAV swarm

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