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

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

科研成果: 期刊稿件文章同行评审

8 引用 (Scopus)

摘要

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.

源语言英语
页(从-至)158-168
页数11
期刊International Journal of Bio-Inspired Computation
19
3
DOI
出版状态已出版 - 2022

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