发表机构
Pôle recherche, AMIAD; UI2S, ENSTA, IP Paris; LARIAD（AMIAD研究中心; 巴黎理工学院ENSTA分校UI2S实验室; LARIAD实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对多无人机探索的间歇性通信问题，提出基于前沿连通性的去中心化图扩展策略，应用于两种区域划分方法，低通信速率下探索效率优于现有方法。
AI 中文摘要
使用多架无人机探索未知环境需要在间歇性通信下进行协调，去中心化操作是基础假设。我们在去中心化框架内提出一种基于前沿连通性的新型探索图扩展策略，用于扩展探索计划并保持智能体间的区域划分稳定且对断开连接及空间布局变化具有鲁棒性。该扩展方法被应用于两种最先进的区域划分方法并在仿真中评估，实验表明，与现有图扩展方法相比，在低通信速率下具有更高的探索效率，性能得到提升。
英文摘要
Exploring unknown environments with multiple UAVs requires coordination under intermittent communication, making decentralized operation a baseline assumption. We propose, within a decentralized framework, a novel exploration graph extension strategy based on frontier connectivity to extend exploration plans and maintain area partitioning among agents stable and robust to disconnections and changes in spatial layout. The proposed extension method is applied to two state-of-the-art area partitioning methods and evaluated in simulation. Experiments show improved performance over existing graph extension approaches with higher exploration efficiency under low communication rate.
