【代表性论文】

[1]   Yan C, Wang C, Zhou H, Xiang X, Wang X and Shen L. Multi-agent reinforcement learning with spatial-temporal attention for flocking with collision avoidance of a scalable fixed-wing UAV fleet[J]. IEEE Transactions on Intelligent Transportation Systems, 2025, 26(2): 1769-1782.

[2]   Yan C, Wang C, Xiang X, Low K H, Wang X, Xu X, Shen L. Collision- avoiding flocking with multiple fixed-wing UAVs in obstacle-cluttered environments: A task-specific curriculum-based MADRL approach[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(8): 10894-10908.

[3]   Yan C, Xiang X, Wang C, Li F, Wang X, Xu X, Shen L. Population- specific curriculum-based MADRL for collision-free flocking with large-scale fixed-wing UAV swarms[J]. Aerospace Science and Technology, 2023, 133:108091.

[4]   Yan C, Wang C, Xiang X, Lan Z, and Jiang Y. Deep reinforcement learning of collision-free flocking policies for multiple fixed-wing UAVs using local situation maps[J]. IEEE Transactions on Industrial Informatics, 2022, 18(2): 1260-1270.

[5]   Yan C, Xiang X, Wang C. Fixed-wing UAVs flocking in continuous spaces: A deep reinforcement learning approach[J]. Robotics and Autonomous Systems, 2020, 131: 103594.

[6]   Yan C, Xiang X, Wang C. Towards real-time path planning through deep reinforcement learning for a UAV in dynamic environments[J]. Journal of Intelligent & Robotic Systems, 2020, 98(2): 297-309. (封面论文)

[7]   Yan C, Low K H, Xiang X, Hu T, and Shen L. Attention-based population- invariant deep reinforcement learning for collision-free flocking with a scalable fixed-wing UAV swarm[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2022: 13730-13736.

[8]   Yan C, Xiang X, Wang C, Lan Z. Flocking and collision avoidance for a dynamic squad of fixed-wing UAVs using deep reinforcement learning [C]//IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2021: 4738-4744.

[9]   闫超, 相晓嘉, 徐昕, 王菖, 周晗, 沈林成. 多智能体深度强化学习及其可扩展性与可迁移性研究综述[J]. 控制与决策, 2022, 37(12): 3083-3102. (封面论文, 当年热文)

[10] 相晓嘉，闫超*，王菖, 尹栋. 基于深度强化学习的固定翼无人机编队协调控制方法[J]. 航空学报, 2021, 42(4): 524009. (高影响力论文)

【指导学生论文】

[1]   Li C#, Yan C#, Xiang X, et al. AMPLE: Automatic progressive learning for orientation unknown ground-to-aerial geo-localization[J]. IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, 2025, 63: 5800115. (共同一作)

[2]   Lan Z, Li Z, Yan C, et al. Adaptive knowledge distillation with attention-based multi-modal fusion for robust dim object detection[J]. IEEE Transactions on Multimedia, 2025, 27: 2083-2096.

[3]   Zhang Y, Yan C, Xiao J, et al. NPE-DRL: Enhancing perception constrained obstacle avoidance with non-expert policy guided reinforcement learning[J]. IEEE Transactions on Artificial Intelligence, 2025, 6(1): 184-198.

[4]   Li C, Yan C, Xiang X, et al. HADGEO: Image based 3-DoF cross-view geo-localization with hard sample mining[C]//IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2024: 3520-3524.

[5]   Sun Y#, Yan C#, Xiang X, et al. Towards end-to-end formation control for robotic fish via deep reinforcement learning with non-expert imitation, Ocean Engineering, 2023, 271: 113811. (共同一作)

[6]   Zhang M, Yan C, Dai W, et al. Tactical conflict resolution in urban airspace for unmanned aerial vehicles operations using attention-based deep reinforcement learning[J]. Green Energy and Intelligent Transportation, 2023, 2(4): 100107.

[7]   Li Z#, Yan C#, Lan Z, et al. MCGRAM: Linking multi-scale CNN with a graph-based recurrent attention model for subject-independent ERP detection[J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2022, 69(12): 5199-5203. (共同一作)

[8]   Lan Z#, Yan C#, Li Z, et al. MACRO: Multi-attention convolutional recurrent model for subject-independent ERP detection[J]. IEEE Signal Processing Letters, 2021, 28: 1505-1509. (共同一作)

[9]  孙懿豪, 闫超, 相晓嘉, 等. 基于分层强化学习的多无人机协同围捕方法[J]. 控制理论与应用, 2025, 42(1): 96-108.