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.

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Institutions

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

Controls
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article

Self‐organizing cooperative hunting for unmanned surface vehicles with constrained kinematics

Jinduo Wang, Qun Deng, Dong Qu, Yan Peng et al.
2 citations
Optimal Control Applications and Methods
Guidance and Control Systems
2.60
article

Self‐organizing cooperative hunting for unmanned surface vehicles with constrained kinematics

Jinduo Wang, Qun Deng, Dong Qu, Yan Peng, Yangmin Xie, Tingke Mo
article en
2 citations

Abstract

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.

Optimal Control Applications and MethodsVol. 46(2)
Shanghai University (CN), Beijing Academy of Artificial Intelligence (CN)
National Key Research and Development Program of China, Program of Shanghai Academic Research Leader
Openalex Percentile: Top 9%
Guidance and Control Systems
2.60
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Self‐organizing cooperative hunting for unmanned surface vehicles with constrained kinematics — Jinduo Wang, Qun Deng, et al. · Optimal Control Applications and Methods (2024) | TGRS Research Map | TGRS