低空协同智能体系架构与关键技术

doi:10.7527/S1000-6893.2026.33756

Abstract

Abstract:

Facing the development demands of the low-altitude economy， the large-scale application of low-altitude aircraft in scenarios such as logistics distribution， urban supervision， emergency rescue， and low-altitude operations places higher requirements on the perception， communication， computing， and intelligence of low-altitude networks. Addressing the issues of insufficient coverage， fragile links， low coordination efficiency， and limited edge resources in traditional terrestrial networks within three-dimensional high-dynamic airspace， this paper reviews the low-altitude collaborative intelligence architecture and key technologies for the 6th Generation of Mobile Communication System （6G） space-air-ground integrated networks. First， it explains the operation mechanism of the dual end-cloud adaptive architecture and its parallel coupling of task flows and knowledge flows； next， it systematically reviews the research progress on key technologies such as cross-domain collaborative perception， heterogeneous dynamic networking， collaborative computing and distributed decision-making， and collaborative learning； further， by combining typical scenarios such as surveillance of unauthorized low-altitude drones， low-altitude network security coverage and resilient information assurance， and low-altitude network operations， it summarizes the application requirements and common challenges of low-altitude collaborative intelligence. The analysis indicates that the key issues faced by low-altitude collaborative intelligence mainly concentrate on perception trustworthiness， connection continuity， decision stability， and continuous learning.

Key words: low-altitude economy, low-altitude intelligent network, unmanned aerial vehicles, collaborative intelligence, dual adaptation of edge and cloud

CLC Number:

V2-9
TN92

Chao DONG, Yuqian JING, Jiahao YOU, Jiajing WU, Honghui JIN, Wei FENG. Architecture and key technologies of low-altitude cooperative intelligence[J]. Acta Aeronautica et Astronautica Sinica, 2026, 47(18): 533756.

Figures/Tables 6

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架构维度	传统集中式云网架构	基础边缘卸载架构	端云双适协同架构
计算负载分布	核心网云端承担100%重载推理	边缘节点承担70%，端侧30%	动态自适应切分；端侧实时推理，云端异步演进
数据传输策略	原始海量数据全量上传	预处理后的特征数据上传	基于价值的信息熵筛选；仅回传困难样本驱动增量学习
拓扑动态适应性	极差；链路断开即导致任务全面停滞	较弱；切换边缘服务器会导致短暂业务中断	极强；支持端侧独立保底运行与模型断点可缝合拆分

Architecture and key technologies of low-altitude cooperative intelligence

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