Self‐organizing cooperative hunting for unmanned surface vehicles with constrained kinematics
Summary The article aims at solving a cooperative hunting problem for multiple unmanned surface vehicles (USVs) subject to constrained kinematics. In order to cooperatively trap the evader into the hunting domain, a velocity model with control variable for the pursuers is firstly proposed according to the Apollonius circle. Then, a flexible self‐organizing control strategy is developed, which enables the pursuers to approach the evader while forming an encirclement. The pursuers can dynamically adapt their strategies in real‐time by choosing the optimal control variable. Additionally, take into account the limitation imposed on the vessel's motion, the optimal control variable with constraint can be obtained by using the particle swarm optimization with log‐barrier method. The simulation results ultimately demonstrate the validity and superiority of the proposed cooperative hunting algorithm.
Authors
- Jinduo Wang (ORCID: https://orcid.org/0009-0002-8082-3893)
- Qun Deng (ORCID: https://orcid.org/0000-0001-8286-2090)
- Dong Qu (ORCID: https://orcid.org/0009-0001-0960-7795)
- Yan Peng (ORCID: https://orcid.org/0000-0001-5003-6923)
- Yangmin Xie (ORCID: https://orcid.org/0000-0002-6517-2917)
- Tingke Mo
Institutions
- Shanghai University (CN)
- Beijing Academy of Artificial Intelligence (CN)
Publication Details
- Journal
- Optimal Control Applications and Methods
- Published
- 2024-08-11
- DOI
- https://doi.org/10.1002/oca.3194
- Citations
- 2
- Primary Topic
- Guidance and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 2.60
Funders
- National Key Research and Development Program of China
- Program of Shanghai Academic Research Leader