论文标题
使用粒子群优化和基于行为的控制，用于最佳多台化临时网络的无人机部署
Deployment of UAVs for Optimal Multihop Ad-hoc Networks Using Particle Swarm Optimization and Behavior-based Control
论文作者
论文摘要
这项研究提出了一种使用多个无人驾驶汽车（UAV）建立最佳的多直接临时网络的方法，以在灾难区提供紧急通信。该方法包括两个阶段，一个阶段使用粒子群优化（PSO）来找到最佳的位置来部署无人机，而另一个使用基于行为的控制器将无人机导航到其分配的位置，而无需在未知环境中与障碍物相撞。已经对与无人机的传感和通信范围相关的几个约束是为了确保所提出的方法在现实世界中的适用性。已经进行了许多来自真实环境加载数据的模拟实验。结果表明，我们提出的方法不仅成功地建立了多台化临时路线，而且还满足了无人机实时部署的要求。
This study proposes an approach for establishing an optimal multihop ad-hoc network using multiple unmanned aerial vehicles (UAVs) to provide emergency communication in disaster areas. The approach includes two stages, one uses particle swarm optimization (PSO) to find optimal positions to deploy UAVs, and the other uses a behavior-based controller to navigate the UAVs to their assigned positions without colliding with obstacles in an unknown environment. Several constraints related to the UAVs' sensing and communication ranges have been imposed to ensure the applicability of the proposed approach in real-world scenarios. A number of simulation experiments with data loaded from real environments have been conducted. The results show that our proposed approach is not only successful in establishing multihop ad-hoc routes but also meets the requirements for real-time deployment of UAVs.
