Pigeon-inspired optimisation-based cooperative target searching for multi-UAV in uncertain environment

Delin Luo, Sijie Li, Jiang Shao, Yang Xu, Yong Liu

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

In this paper, the multi-UAV cooperative target searching problem is investigated and a close loop path planning method is developed for UAVs in uncertain environment. The proposed method includes two consecutive parts, the multi-UAV cooperative target search algorithm developed based on cooperative pigeon-inspired optimisation (CPIO) and the base returning algorithm for each UAV based on artificial potential field (APF) method. Firstly, a concerned regional environment and the initial search probability map models are established. Then, by applying the rolling prediction strategy, the cooperative target search paths for multiple UAVs are generated by utilising the proposed CPIO. With this method, UAVs can reinforce target search in the key areas in a cooperative way and avoid flying into the no-fly zones. In the meanwhile, the Bayesian theorem is used to constantly update the search probability map in each search step. Finally, at the end of the target search phase, an optimised safe path is generated for each UAV returning back to its original by using the APF method. Simulations are performed and the results demonstrate that the proposed approach is effective for multiple UAVs carrying out cooperative target search task in a complex environment.

Original languageEnglish
Pages (from-to)158-168
Number of pages11
JournalInternational Journal of Bio-Inspired Computation
Volume19
Issue number3
DOIs
StatePublished - 2022

Keywords

  • APF
  • artificial potential field
  • cooperative search
  • multi-UAV
  • pigeon-inspired algorithm

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