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A leader–follower formation control approach for target hunting by multiple autonomous underwater vehicle in three-dimensional underwater environments

机译:三维水下环境中多个自治水下车辆目标狩猎的领导者 - 跟随器形成方法

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As one of the challenging tasks of multiple autonomous underwater vehicles systems, the realization of target hunting is the great significance. The multiple autonomous underwater vehicle target hunting is studied in this article. In some research, because the hunting members cannot reach the hunting point at the same time, the hunting time is long or the target escapes. To improve the efficiency of the target hunting, the leader–follower formation algorithm is introduced. Firstly, the task is assigned based on the distance between the autonomous underwater vehicle and the target. Then, the autonomous underwater vehicles with the same task are formed based on leader–follower mode, and the formation is kept to track the target. In the final capture phase, multiple autonomous underwater vehicle system use angle matching algorithm to round up target. The simulation results show that the proposed algorithm can effectively accomplish the target hunting task, save the hunting time, and avoid the target escape. Compared with the bioinspired neural network algorithm, the proposed algorithm shows better performance.
机译:作为多个自主水下车辆系统的具有挑战性的任务之一,目标狩猎的实现是具有重要意义。本文研究了多个自主水下车辆目标狩猎。在一些研究中,因为狩猎成员同时无法达到狩猎点,所以狩猎时间很长或目标逃脱。为了提高目标狩猎的效率,介绍了领导跟随地层算法。首先,任务基于自动水下车辆与目标之间的距离来分配。然后,基于引导跟随器模式形成具有相同任务的自主水下车辆,并且形成形成以跟踪目标。在最终捕获阶段,多个自主水下车辆系统使用角度匹配算法来舍入目标。仿真结果表明,该算法可以有效地完成目标狩猎任务,保存狩猎时间,避免目标逃生。与BioInspired神经网络算法相比,所提出的算法显示出更好的性能。

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