An Intent Recognition Method for Aerial Swarm Based on Attention Pooling Mechanism

Hui He, Zhihong Peng*, Peiqiao Shang, Wenjie Wang, Xiaoshuai Pei

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

摘要

In the realm of unmanned aerial vehicle (UAV) swarm intent recognition, conventional approaches predominantly focus on the attributes derived from singular targets at discrete instances. This trend leads to a significant limitation: the inability to effectively harness and capture the collective feature information of the entire swarm over temporal sequences. To address this gap, this study introduces a comprehensive end-to-end UAV swarm intent recognition approach. Initially, this method utilizes the distance threat coefficient and angular threat coefficient between UAVs to construct the graphical structural representation of the UAV swarm. Subsequently, an innovative deep learning framework, designated as attention-pool based on graph attention network and long short-term memory, which integrates a graph attention network, a novel graph pooling strategy, and a long short-term memory, is developed. This architecture can process the graphically structured data derived from the swarm modeling and accurately deduce the collective intent. Through experimental validation and analyses against existing methodologies, as well as ablation studies, it is evidenced that the model outperforms state-of-the-art methods in terms of accuracy of intent recognition.

源语言英语
页(从-至)5-11
页数7
期刊Journal of Advanced Computational Intelligence and Intelligent Informatics
29
1
DOI
出版状态已出版 - 1月 2025

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引用此

He, H., Peng, Z., Shang, P., Wang, W., & Pei, X. (2025). An Intent Recognition Method for Aerial Swarm Based on Attention Pooling Mechanism. Journal of Advanced Computational Intelligence and Intelligent Informatics, 29(1), 5-11. https://doi.org/10.20965/jaciii.2025.p0005