[1]      面向混合任务场景的多水下机器人系统在线任务规划方法研究, 62373318, 国家自然科学基金面上项目, 2024.01-2027.12, 50万元, 项目负责人.

[2]      基于对抗性MAB理论的异构多水下机器人系统分布式任务规划, 62003295, 国家自然科学基金青年项目, 2021.01-2023.12, 24万元, 项目负责人.

[3]      深远海低成本、长航时协同导航定位系统关键技术研究, 41976182, 国家自然科学基金面上项目, 2020.01-2023.12, 16.25万元, 子课题负责人.

[4]      基于轻量化需求的水声协作通信网络在线联合资源优化, F2022203025, 河北省自然科学基金面上项目, 2022.01-2024.12,10万元, 项目负责人.

[5]      基于机器学习的水下无线传感器网络资源分配与优化, F2019203031, 河北省自然科学基金青年项目, 2019.01-2021.12, 6万元, 项目负责人.

[6]      未知海洋环境下水声协作通信网络资源分配算法研究, 2020M670690, 中国博士后科学基金项目, 2020.07-2020.12, 8万元, 项目负责人.

[7]      面向未知环境的水声协作通信网络联合资源分配算法研究, B2019003019, 河北省博士后择优资助科研项目, 2019.05-2020.09, 3万元, 项目负责人.

[8]      复杂海洋环境下水声协作通信网络分布式多通信策略优化方法研究, QN2020301, 河北省教育厅项目, 2020-2022, 3万元, 项目负责人.

代表性5项学术成果

[1]   Han Song, Zhao Huan, Li Xinbin, Yu junzhi, Zhang Tongwei, Liu Zhixin. Joint Multiple Resources Allocation for Underwater Acoustic Cooperative Communication in Time-Varying IoUT Systems: A Double Closed-Loop Adversarial Bandit Approach[J]. IEEE Internet of Things Journal, 2023, 35(2):1833-1846. (SCI 1区TOP IF:10.6)

[2]   Han Song, Zhang Tao, Li Xinbin, Yu junzhi, Zhang Tongwei, Liu Zhixin. The Unified Task Assignment for Underwater Data Collection With Multi-AUV System: A Reinforced Self-Organizing Mapping Approach[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024. 11(2):2573-2587. (SCI 1区TOP IF:10.4)

[3]   Han Song, Zhao Huan, Li Xinbin, Yu junzhi, Zhao Haihong, Liu Zhixin, Joint Resource Allocation for Time-Varying Underwater Acoustic Communication System: A Self-Reflection Adversarial Bandit Approach[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024, 54(4):2227-2240. (SCI 1区TOP IF:8.7)

[4]   Han Song, Zhao Jiaao, Li Xinbin, Yu Junzhi, Wang Shuili, Liu Zhixin. Online Path Planning for AUV in Dynamic Ocean Scenarios: A Lightweight Neural Dynamics Network Approach[J], IEEE Transactions on Intelligent Vehicles, 2024. DOI: 10.1109/TIV.2024.3356529. (SCI 1区IF:8.2)

[5]   Han Song, Li Luo, Li Xinbin, Liu Zhixin, Yan Lei, Zhang Tongwei. Joint Relay Selection and Power Allocation for Time-Varying Energy Harvesting-Driven UASNs: A Stratified Reinforcement Learning Approach[J]. IEEE Sensors Journal, 2022, 22(20): 20063-20072. (SCI 2区 IF:4.33)