arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2602.10029cs.NIcs.MA
收藏

抗扰动的拓扑感知协调用于动态3D无人机网络中的节点故障

Resilient Topology-Aware Coordination for Dynamic 3D UAV Networks under Node Failure

National Chung Cheng University(中正大学);Advanced Institute of Manufacturing with High-tech Innovations (AIM-HI), National Chung Cheng University(中正大学先进制造与高技术创新研究院)

Chuan-Chi Lai

AI总结:

本文提出拓扑感知图MAPPO框架,通过自主3D空间重新配置提升动态无人机网络在节点故障下的鲁棒性和生存能力。

摘要:

在意外硬件故障下确保持续的服务覆盖是3D空天地一体化网络的基本挑战。尽管多智能体强化学习促进了自主协调,但传统架构往往缺乏对突然拓扑变形的韧性。本文提出了拓扑感知图MAPPO(TAG-MAPPO)框架,通过自主的3D空间重新配置来增强系统的生存能力。我们的框架集成了基于图的特征聚合与残差自体状态融合机制,以捕捉复杂的智能体依赖关系。为了实现结构的鲁棒性,我们引入了一种随机观察洗牌机制,通过打破坐标-索引依赖性,促进对智能体种群波动的强泛化能力。在异构环境中进行了广泛的模拟,包括15米每秒的高速移动,结果表明TAG-MAPPO在多层感知机基线中表现显著优越。具体而言,该框架通过减少高达50%的冗余切换,同时保持优越的能效。最值得注意的是,TAG-MAPPO表现出卓越的自愈能力,在15个时间步内恢复超过90%的故障前覆盖。在密集城市场景中,该框架在故障后公平指数上超过了其原始四UAV配置,通过自主解决服务重叠和干扰实现了这一目标。这些发现证实了拓扑感知协调对于6G空中网络韧性的重要性。

英文摘要:

Ensuring continuous service coverage under unexpected hardware failures is a fundamental challenge for 3D Aerial-Ground Integrated Networks. Although Multi-Agent Reinforcement Learning facilitates autonomous coordination, traditional architectures often lack resilience to sudden topology deformations. This paper proposes the Topology-Aware Graph MAPPO (TAG-MAPPO) framework to enhance system survivability through autonomous 3D spatial reconfiguration. Our framework integrates graph-based feature aggregation with a residual ego-state fusion mechanism to capture intricate inter-agent dependencies. To achieve structural robustness, we introduce a Random Observation Shuffling mechanism that fosters strong generalization to agent population fluctuations by breaking coordinate-index dependencies. Extensive simulations across heterogeneous environments, including high-speed mobility at 15 meters per second, demonstrate that TAG-MAPPO significantly outperforms Multi-Layer Perceptron baselines. Specifically, the framework reduces redundant handoffs by up to 50 percent while maintaining superior energy efficiency. Most notably, TAG-MAPPO exhibits exceptional self-healing capabilities, restoring over 90 percent of pre-failure coverage within 15 time steps. In dense urban scenarios, the framework achieves a post-failure fairness index surpassing its original four-UAV configuration by autonomously resolving service overlaps and interference. These findings confirm that topology-aware coordination is essential for resilient 6G aerial networks.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑