Erkalkan Ercan, Topuz Vedat, Buldu Ali
Department of Computer Technologies, Vocational School of Technical Sciences, Marmara University, 34865 Kartal, İstanbul, Turkey.
Department of Computer Hardware, Department of Computer Engineering, Faculty of Technology, Marmara University, 34840 Maltepe, İstanbul, Turkey.
Sensors (Basel). 2024 Dec 9;24(23):7859. doi: 10.3390/s24237859.
Unmanned Aerial Vehicles (UAVs) have become essential tools across various sectors due to their versatility and advanced capabilities in autonomy, perception, and networking. Despite over a decade of experimental efforts in multi-UAV systems, substantial theoretical challenges concerning coordination mechanisms still need to be solved, particularly in maintaining network connectivity and optimizing routing. Current research has revealed the absence of an efficient algorithm tailored for the routing problem of multiple UAVs connected to a central station, especially under the constraints of maintaining constant network connectivity and minimizing the average goal revisit time. This paper proposes a heuristic routing algorithm for multiple UAV systems to address the return visit challenge in flying ad hoc networks (FANETs) linked to a central station. Our approach introduces a composite valuation function for target prioritization and a mathematical model for task assignment with relay allocation, allowing any UAV to visit various objectives and gain an advantage or incur a cost for each. We exclusively utilized a simulation environment to mimic UAV operations, assessing communication range, connectivity, and routing performance. Extensive simulations demonstrate that our routing algorithm remains efficient in the face of frequent topological alterations in the network, showing robustness against dynamic environments and superior performance compared to existing methods. This paper presents different approaches to efficiently directing UAVs and explains how heuristic algorithms can enhance our understanding and improve current methods for task assignments.
无人机（UAVs）因其多功能性以及在自主性、感知和网络方面的先进能力，已成为各个领域的重要工具。尽管在多无人机系统方面进行了十多年的实验，但关于协调机制的重大理论挑战仍有待解决，特别是在维持网络连接性和优化路由方面。当前的研究表明，缺乏一种专门针对连接到中央站的多架无人机的路由问题的高效算法，尤其是在保持恒定网络连接性和最小化平均目标重访时间的约束条件下。本文提出了一种针对多无人机系统的启发式路由算法，以解决与中央站相连的移动自组织网络（FANETs）中的重访挑战。我们的方法引入了用于目标优先级排序的复合评估函数以及带有中继分配的任务分配数学模型，允许任何无人机访问各种目标，并为每个目标获取优势或产生成本。我们专门利用模拟环境来模拟无人机操作，评估通信范围、连接性和路由性能。大量模拟表明，我们的路由算法在面对网络中频繁的拓扑变化时仍然高效，展现出对动态环境的鲁棒性以及与现有方法相比的卓越性能。本文介绍了有效引导无人机的不同方法，并解释了启发式算法如何增进我们的理解并改进当前的任务分配方法。
