未知环境下多自主水下航行器目标搜索方法

Target search of multiple autonomous underwater vehicles in an unknown environment

针对未知复杂环境下,传统搜索模式或离线设计全局优化航迹的自主水下航行器搜索方法中,搜索效率低,定位精度不稳定,环境适应能力差等问题,本文提出一种基于动态预测的多自主水下航行器协同自适应目标搜索方法,该方法分为3种模式:有目标模式,根据获取声呐视域中的目标信息进行自适应的实时目标搜索;无目标模式,利用分区域策略辅助区域搜索覆盖、协同规划任务;避障模式,利用改进的动态窗口法实时面对复杂的障碍威胁;根据不同的水下环境,3种模式间交替切换执行,完成未知水下环境的目标搜索。仿真结果表明:该方法能够应对未知水下的不确定信息,保障目标状态信息的可信区间,具有环境适应性和搜索高效性。

The autonomous underwater vehicle(AUV)search method in traditional complex search mode or offline design global optimization track features a low search efficiency,unstable positioning accuracy,and poor environmental adaptability.A multi-AUV collaborative adaptive target search method based on the dynamic prediction is proposed.The method is divided into three modes:target mode,which is used for real-time target search according to the acquired target information in the sonar field of view;no-target mode,which uses sub-region strategy-assisted area search coverage and plans tasks collaboratively;obstacle avoidance mode,which uses the improved dynamic window method to face complex obstacle threats in real time.According to different underwater environments,the method alternately switches between the three modes to complete the target search in an unknown underwater environment.The simulation results show that the proposed method can cope with uncertain underwater information and guarantee the confidence interval of the target state information.The proposed method also exhibits environmental adaptability and high efficiency in searching.