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首页> 外文期刊>Ocean Engineering >Coordinated path planning for an unmanned aerial-aquatic vehicle (UAAV) and an autonomous underwater vehicle (AUV) in an underwater target strike mission
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Coordinated path planning for an unmanned aerial-aquatic vehicle (UAAV) and an autonomous underwater vehicle (AUV) in an underwater target strike mission

机译：水下目标打击任务中无人水上飞行器（UAAV）和无人水下航行器（AUV）的协调路径规划

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摘要

Unmanned system has become more and more popular as it can adapt to diverse environments and has prospective applications. Especially, the coordination among heterogeneous vehicles is capable of completing complicated tasks, which is often beyond the ability of homogeneous vehicles. In this paper, the underwater target strike mission is concentrated, and the mission is completed by the coordination between a UAAV and an AUV. UAAV and AUV are deployed in this mission because UAAV has strong search ability in air and can communicate with AUV directly after it dives into water. Firstly, to decompose the problem, the mission is divided into two phases, i.e., single flying of UAAV and underwater coordination between UAAV and AUV. In the coordinated path planning model, the motion of vehicles, the constraints in different media and the optimization index in each phase are all formulated into mathematical forms. Based on the particle swarm optimization (PSO) algorithm, the collocation points are used to determine the locations of control variables. Those points can reduce the computation load and improve the solution quality, and they are distributed by height and moment according to the forms of constraints in each phase. Besides, the strategy of addressing infeasible solutions is generated to guarantee the normal operation of PSO-based algorithm. Simulation results demonstrate that the proposed two-phase coordinated path planning method can generate coordinated paths, and the obtained results is very close to the optimal solution in theory. Compared to the whole method, the two-phase method can better deal with the complicated constraints in each phase.
机译：无人系统由于能够适应各种环境并具有潜在的应用而变得越来越流行。特别是，异构车辆之间的协调能够完成复杂的任务，而这往往超出了同类车辆的能力。在本文中，水下目标打击任务是集中的，并且该任务是通过UAAV和AUV之间的协调来完成的。 UAAV和AUV被部署在此任务中是因为UAAV在空中具有强大的搜索能力，并且在潜入水中后可以直接与AUV通信。首先，为了分解问题，任务分为两个阶段，即UAAV的单次飞行和UAAV与AUV之间的水下协调。在协调路径规划模型中，车辆的运动，不同介质中的约束以及每个阶段的优化指标都以数学形式表示。基于粒子群优化（PSO）算法，并置点用于确定控制变量的位置。这些点可以减少计算量并提高求解质量，并且根据每个阶段的约束形式按高度和矩进行分布。此外，还提出了解决不可行解决方案的策略，以保证基于PSO的算法的正常运行。仿真结果表明，所提出的两阶段协调路径规划方法可以生成协调路径，所获得的结果在理论上与最优解非常接近。与整个方法相比，两阶段方法可以更好地处理每个阶段中的复杂约束。

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