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MURM-A:基于无线电地图和复杂网络的蜂连接多无人机的综合路径规划方案中的改进A

Yanming Chai¹, Qibin He¹, Yapeng Wang¹

¹Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR 999078, China.

Sensors (Basel, Switzerland)

|February 13, 2026

概括

这项研究介绍了MURM-A*,这是一个改进的A*算法,用于多个蜂连接的无人机 (UAV). 它通过整合无线电地图和复杂网络来增强路径规划,确保城市空域的飞行安全和网络连接.

科学领域:

机器人技术和自主系统
网络工程网络工程
航空航天工程航空航天工程

背景情况:

连接到蜂网络的无人机 (UAV) 需要持续的网络连接和在密集的城市空域中的飞行安全.
现有的路线规划方法在处理环境数据,避开障碍物,飞行动态和多无人机冲突解决方面扎.
传统的A*算法的局限性阻碍了对无人机的路径效率和无线电质量的同时优化.

研究的目的:

为多个蜂连接的无人机开发一个全面的路径规划方案.
解决环境地图数据处理和多约束路径规划现有研究的局限性.
改善复杂的城市无线电环境中无人机的飞行安全和网络连接.

主要方法:

使用复杂网络理论,环境数据和无线电地图构建了路径规划模型.
开发了一种改进的A*算法 (MURM-A*),用于多无人机场景.
环境表示与对增强处理的算法搜索分开.

主要成果:

MURM-A*算法有效地避免了障碍物,并防止了无人机路径之间的空间冲突.
与深度强化学习 (DRL) 相比,实现了路径效率和无线电质量的联合优化,减少了无线电断电时间.
与DRL相比,路线规划模型改善了环境信息的识别和减少了建模时间.

结论:

拟议的系统框架为复杂无线电环境中的多个蜂连接无人机提供可靠的路径规划.
在无人机路径规划方面,MURM-A*为传统的A*和DRL方法提供了有效和高效的替代方案.
该研究为未来的无人机路径规划研究建立了一个结构良好的,可扩展的框架.

关键词:

一个A级明星.复杂的网络复杂的网络.多个无人机的UAV.路径规划路径规划路径规划路径规划模型模型的路径规划模型无线电地图无线电地图无人驾驶飞行器 (UAV) 是一种无人驾驶飞行器.

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