Autonomous Decision-Making and Control Theory for Unmanned Systems Based on Artificial Intelligence (基于人工智能的无人系统自主决策与控制理论)
Chair: 
Ping Wang, Sun Yat-sen University, China
Co-chair: 
Xiaoliang Wang, Shanghai Jiao Tong University, China
Keywords: | Topics (Include but are not limited to): |
· Unmanned Systems (无人系统) · Artificial Intelligence (人工智能) · Autonomous Decision-Making (自主决策) · Intelligent Control (智能控制) · Reinforcement Learning (强化学习) · Robustness Optimization (鲁棒性优化) · Environmental Perception (环境感知) | · Environmental Perception (无人系统的环境感知) · Dynamic Modeling (动态建模) · Path Planning (路径规划) · Collaborative Control (协同控制) · Robustness Optimization (鲁棒性优化) · Real-time Decision-making (实时决策) · AI-driven Innovative Methods for Unmanned Systems (人工智能驱动的无人系统创新方法) |
Summary:
· With the rapid development of artificial intelligence (AI) technologies, significant progress has been made in the field of autonomous decision-making and control for unmanned systems. This special topic focuses on the application of AI technologies in unmanned systems, exploring how machine learning, deep learning, reinforcement learning, and other methods can enable intelligent decision-making and efficient control. Research areas include but are not limited to: environmental perception, dynamic modeling, path planning, collaborative control, robustness optimization, and real-time decision-making for unmanned systems. The goal of this topic is to promote the deep integration of AI and unmanned system control, providing theoretical support and technical solutions for the autonomy and intelligence of unmanned systems in complex environments.
· 随着人工智能技术的快速发展，无人系统在自主决策与控制领域取得了显著进展。本专题聚焦于人工智能技术在无人系统中的应用，探讨如何通过机器学习、深度学习、强化学习等方法实现无人系统的智能化决策与高效控制。研究内容包括但不限于：无人系统的环境感知、动态建模、路径规划、协同控制、鲁棒性优化以及实时决策等。本专题旨在推动人工智能与无人系统控制的深度融合，为无人系统在复杂环境下的自主化、智能化提供理论支持和技术解决方案。