Underwater Target Capture based on Heterogeneous Unmanned System Collaboration

Due to motion constraints, an underwater unmanned vehicle (UUV) is not sufficient to efficiently complete large-scale underwater target capture tasks. By coordinating multiple unmanned devices, the success rate of target capture can be greatly improved. Compared to the collaboration of homogeneous unmanned devices, the collaboration of heterogeneous unmanned devices can provide more abundant spatiotemporal information, which helps to better accomplish the tasks. To improve work efficiency, this paper proposes a strategy for underwater target capture based on the collaboration of heterogeneous unmanned devices. Firstly, a heterogeneous unmanned system composed of unmanned aerial vehicle (UAV), unmanned surface vehicle (USV), and UUVs is designed for the task of target capture. Secondly, under the constraints of communication and energy, a full coverage path planning scheme for the collaboration of UAV and USV is proposed to increase the observation range of UAV within a unit of time. Finally, the UUVs utilize an adaptive grey wolf optimizer (GWO) algorithm to capture the underwater target. Simulation results demonstrate that the efficiency of target capture is improved through the collaboration of UAV, USV, and UUVs. The proposed adaptive GWO algorithm effectively addresses the issue of premature convergence in the target capture process.