Special Session VIII

Intelligent Decision Making and Collaborative Mission Planning Methods for Advanced Vehicles
先进飞行器智能决策与协同任务规划方法

Introduction:

Intelligent Decision Making and Mission Allocation for Advanced Vehicles is a cutting-edge research field oriented towards integrated air-space intelligent systems. By integrating artificial intelligence with distributed control theory, this initiative addresses critical challenges including multi-source information fusion, real-time task allocation, and anti-jamming cooperative trajectory optimization. The conference aims to collaborate with experts, scholars, and engineers worldwide to demonstrate and share innovative achievements in intelligent algorithm design, digital twin verification platforms, and multi-agent collaborative frameworks for advanced aerospace vehicles.
The topics of this session include but are not limited to: intelligent decision-making models for advanced aerospace vehicles, perception and decision-making in unknown environments, hybrid augmented intelligence optimization algorithms, mission allocation and path planning, offensive-defensive game-theoretic decision-making, intelligent firepower decision-making and allocation, as well as related innovative applications and emerging research trends.

先进飞行器的智能决策与任务分配是一个面向空天智能系统前沿研究领域。通过人工智能与分布式控制理论融合,攻克多源信息融合、实时任务分配、抗干扰协同航迹优化等核心问题。本次会议的目的是与来自世界各地的专家、学者和工程师合作,展示并分享智能算法设计、数字孪生验证平台及多智能体协同框架等创新性成果在先进飞行器上的应用。
本专题包括但不限于:先进飞行器智能决策模型、未知环境感知与决策、混合增强智能优化算法、任务分配与航路规划、攻防博弈决策、智能火力决策与分配以及相关的创新应用和新的研究趋势。

Organizers:

Tongle Zhou, Nanjing University of Aeronautics and Astronautics, China

Tongle Zhou received his Ph.D. degree in in control theory and control engineering from the Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, China. He is currently a Lecturer with the College of Automation Engineering. He has published more than 20 academic papers, including high-quality ones in internationally renowned journals. He presides over many scientific research projects, such as the National Natural Science Foundation of China, the National Natural Science Foundation of Jiangsu Province, the China Postdoctoral Science Foundation, the National Defense Science, Technology and Industry Bureau Stability Support Project. His current research interests include intelligent mission assignment and decision-making for advanced vehicles, intelligent fire control and decision making, and applications of hybrid augmented intelligence algorithms.

Zengliang Han, Nanjing University of Aeronautics and Astronautics, China

Zengliang Han received his Ph.D. degree in in control theory and control engineering from the Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, China. He is currently an Assistant Researcher with the College of Automation Engineering. He has published more than 20 academic papers, including high-quality ones in internationally renowned journals. He presides over many scientific research projects, such as the National Natural Science Foundation of China, the National Natural Science Foundation of Jiangsu Province, the China Postdoctoral Science Foundation, the National Defense Science, Technology and Industry Bureau Stability Support Project. His current research interests include intelligent mission assignment and path planning for advanced vehicles, intelligent fire control and decision making, and applications of hybrid augmented intelligence algorithms.

Min Wan, Nanjing University of Aeronautics and Astronautics, China

Min Wan received her Ph.D. degree in control theory and control engineering from Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, China. She is currently a senior laboratory technician with the College of Automation Engineering, NUAA. She has been long engaged in flight control of UAV, neural network control, adaptive control, and fault-tolerant control. She presides over one project from National Key Laboratory of Space Intelligent Control, and participates in many scientific research projects such as the National Natural Science Foundation of China, and National Key Research and Development Program. At present, she has published more than 10 papers.

Yuqin Dou, Nanjing University of Posts and Telecommunications, China

Yuqin Dou is currently a Lecturer at the School of Nanjing University of Posts and Telecommunications, Nanjing, China. His research focuses on embedded systems, UAV optimization theory, hardware security, and approximate computing. Dr. Dou has authored over 10 peer-reviewed publications in prestigious journals, including IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I), IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), and IEEE Transactions on Emerging Topics in Computing (TETC). He pursued joint doctoral training at Queen's University Belfast, UK, and Nanjing University of Aeronautics and Astronautics, China, as part of his academic development.

Submission Guideline:

Please submit your manuscript via Online Submission System: https://easychair.org/conferences/?conf=rcae2025
Please choose Special Session: Intelligent Decision Making and Collaborative Mission Planning Methods for Advanced Vehicles