• Unmanned Aerial Vehicles (无人飞行器)
• Distributed Control (分布式控制)
• Trajectory Planning and Optimization (轨迹规划与优化)
• Task Allocation and Scheduling (任务分配与调度)
• System Identification and Modeling (系统辨识与建模)
• Multi-UAV Cooperative Systems (多机协同系统)

• System Identification and Dynamic Modeling (系统辨识与动力学建模)
• Trajectory Planning and Optimization (轨迹规划与优化)
• Task Allocation and Scheduling (任务分配与调度)
• Distributed Optimization and Control (分布式优化与控制)
• Intelligent Navigation and Multi-source Information Fusion (智能导航与多源信息融合)
• Swarm Game and Distributed Decision-Making (集群博弈与分布式决策)

This invited session focuses on the modeling, optimization, and control of Unmanned Aerial Vehicle (UAV) systems, with emphasis on multi-UAV cooperation and distributed architectures. Multi-UAV cooperative systems have become a frontier research topic in autonomous systems due to their significant advantages in robustness, coverage, and sensing capability. However, achieving efficient cooperative operations still faces substantial challenges. In particular, the tight coupling between high-level task allocation and low-level trajectory planning, and how to achieve joint optimization under communication constraints, environmental uncertainties, and real-time computational demands, represents a critical scientific issue to be addressed. This session invites original contributions on topics including system identification and dynamic modeling, trajectory planning and optimization, task allocation and scheduling, distributed optimization and control, intelligent navigation and multi-source information fusion, and swarm game and distributed decision-making. The session aims to bring together cutting-edge research outcomes and provide valuable references for the theoretical development and practical applications of distributed coordination and swarm autonomous control.

本专场聚焦无人飞行器系统的建模、优化与控制，重点围绕多无人飞行器协同与分布式架构展开。多无人飞行器协同系统因其在鲁棒性、覆盖范围和感知能力上的显著优势，已成为自主系统领域的前沿热点。然而，高效协同运行的实现仍面临重大挑战，尤其是高层任务分配与低层轨迹规划之间的强耦合问题，如何在通信约束、环境不确定性与实时计算需求下实现联合优化，是亟待解决的关键科学问题之一。本专场诚邀原创稿件，主题涵盖辨识与动力学建模、轨迹规划与优化、任务分配与调度、分布式优化与控制、智能导航与多源信息融合、集群博弈与分布式决策等方向，旨在汇聚前沿研究成果，为分布式协同与集群自主控制的理论发展与应用实践提供有益参考。