姓名：肖剑        邮箱：969559739@qq.com

性别：男

出生年月：1993年1月

籍贯：湖南衡阳

兴趣爱好：羽毛球、篮球

加盟实验室时间：2020.9

导师：王卓然教授

攻博专业：信息与通信工程          科研方向：机器学习与图像处理

学位论文（博）题目：复杂动态环境下多智能体自主协同控制方法研究

 

在校期间主持和参加科研课题：

[1] 四川省自然科学基金面上项目，2022NSFSC0460 ,“复杂环境下基于强化学习的多智能体集群控制方法研究”，2022/01-2023/12, [参与]

[2] 四川省自然科学基金面上项目，2023NSFSC0492,“面向调频连续波激光测距系统的数据驱动控制方法研究”，2023/01-2024/12, [参与]

 

在校期间科研成果：

[1] Xiao J, Huang C, Yuan G, et al. A model learning based multi-agent flocking collaborative control method for stochastic communication environment. IEEE Transactions on Industrial Informatics, 2024, 20(6): 8896-8906.

[2] Xiao J, Wang Z, He J, et al. A graph neural network based deep reinforcement learning algorithm for multi-agent leader-follower flocking. Information Sciences, 2023, 641: 119074. 

[3] Xiao J, Yuan G, He J, et al. Graph attention mechanism based reinforcement learning for multi-agent flocking control in communication-restricted environment. Information Sciences, 2023, 620: 142-157. 

[4] Xiao J, Yuan G, Wang Z. A multi-agent flocking collaborative control method for stochastic dynamic environment via graph attention autoencoder based reinforcement learning. Neurocomputing, 2023, 549: 126379.

[5] Xiao J, Yuan G, Xue Y, et al. A deep reinforcement learning based distributed multi-UAV dynamic area coverage algorithm for complex environment[J]. Neurocomputing, 2024, 595: 127904.

[6] Xiao J, Wang Z, Wang Y, et al. An agent motion model construction method based on sequential attention neural network //2023 3rd International Conference on Artificial Intelligence, Automation and Algorithms. 2023: 36-43. 

[7] Yuan G, Xiao J, He J, et al. Multi-agent cooperative area coverage: a two-stage planning approach based on reinforcement learning. Information Sciences, 2024.

[8] Wang G, Xiao J, R Xue, et al. A multi-group multi-agent system based on reinforcement learning and flocking. International Journal of Control, Automation and Systems, 2022, 20(7): 2364-2378.

[9] Li B, Zhang H, Xiao J*, et al. Energy-efficient multi-agent cooperative search control based on deep reinforcement learning on uneven terrains//2022 IEEE 6th Information Technology and Mechatronics Engineering Conference (ITOEC). IEEE, 2022, 6: 1384-1388.

[10] Tang Y, Hu W, Xiao J, et al. Reinforcement learning based efficiency optimization scheme for the DAB DC-DC converter with triple-phase-shift modulation, IEEE Transactions on Industrial Electronics, 2020, 8(68): 7350-7361.

[11] Tang Y, Cao D, Xiao J, et al. AI-aided power electronic converters automatic online real-time efficiency optimization method. Fundamental Research, 2023.

[12] Zhao H, Yuan G, Xiao J, et al. Linearization of nonlinear frequency modulated continuous wave generation using model-based reinforcement learning. Optics Express, 2022, 30(12): 20647-20658. 

[13] Tang Y, Hu W, Xiao J, et al. RL-ANN based minimum-current-stress scheme for the dual active bridge converter with triple-phase-shift control, IEEE Journal of Emerging and Selected Topics in Power Electronics, 2021, 10(1): 673-689.

 

获奖及荣誉：

2017年，小型四旋翼自主导航，罗麦杯第三届中国研究生未来飞行器创新大赛二等奖。

2018年，小型四旋翼视觉导航系统设计，十三届中国研究生电子设计竞赛西南赛区团队二等奖。