Title: Adaptive Intelligent Robotic Control Using Fuzzy Deep, Broad and Reinforcement Learning Techniques
报告题目：基于模糊深度/宽度/强化学习技术的自适应智能机器人控制
Abstract: Deep learning (DL) and reinforcement learning (RL) have been widely investigated and applied for many engineering applications. Broad learning systems (BLSs) have been shown to work as an effective and efficient incremental learning without the need for deep architecture, thus giving a new paradigm and learning system for AI systems. By incorporating with the merits of DL, RL, variant BLSs and fuzzy logics, this talk will present you fuzzy DL-based, BLS-based and RL-based control frameworks for autonomous mobile robots (AMRs) and multirobots. In the talk, some advances on fuzzy DL NN, fuzzy BLSs and fuzzy reinforcement learning systems are first mentioned, their applications to UAVs, wheeled AMRs and multirobots are discussed in some detail. Experimental results and videos are provided to illustrate the merits of the proposed fuzzy DL-based, BLS-based and RL-based control frameworks. Last but not least, some perspective topics on fuzzy deep, broad and reinforcement learning methods are recommended for future research.
摘要：深度学习（DL）与强化学习（RL）已在众多工程应用领域得到广泛研究和应用。而宽度学习系统（BLS）作为一种无需深度架构的高效增量学习方法，为人工智能系统提供了全新范式。本次报告将融合深度学习、强化学习、多样化宽度学习系统及模糊逻辑的优势，重点阐述基于模糊深度学习、宽度学习及强化学习的自主移动机器人（AMR）与多机器人系统控制框架。内容将涵盖模糊深度神经网络、模糊宽度学习系统及模糊强化学习系统的最新进展，并详细探讨其在无人机、轮式自主移动机器人及多机器人系统的应用。通过实验数据与视频演示，将直观展示所提出的三类模糊控制框架的优越性。最后针对模糊深度/宽度/强化学习方法的未来研究方向提出若干前瞻性课题建议。
Bio: Ching-Chih Tsai received the Diploma in the Department of Electrical Engineering from the National Taipei University of Technology, Taipei City, Taiwan Province, China, in 1981, the M.S. degree in the Institute of Control Engineering from National Chiao Tung University, Taiwan Province, China, in 1986, and the Ph. D degree in the Department of Electrical Engineering from Northwestern University, Evanston, IL, USA, in 1991. He is currently a Life Distinguished Professor in the Department of Electrical Engineering at National Chung Hsing University (NCHU), Taiwan Province, China. He served as Dean of College of Electrical Engineering and Computer Science, NCHU, since August, 2024. He has published and co-authored more than 700 technical articles and received many awards and recognitions from international conferences supported by IEEE. His current research interests include intelligent control, smart mobile robotics and automation intelligence with their applications to service and industrial robots, semiconductor manufacturing and AI-based control systems. He is a Fellow of IEEE, IET, CACS, RST, and TFSA.
简介：蔡清池教授于1981年在中国台湾省台北市的台北科技大学电机工程系获得学士学位，1986年在中国台湾省新竹市的交通大学控制工程研究所获得硕士学位，1991年在美国伊利诺伊州埃文斯顿的西北大学电机工程系获得博士学位。他目前是中国台湾省台中市的中兴大学电机工程系的终身杰出教授，担任中兴大学电机工程与计算机科学学院院长。他已发表和合著了700多篇技术文章，主要研究领域包括智能控制、智能移动机器人和自动化智能及其在服务机器人和工业机器人、半导体制造和基于人工智能的控制系统中的应用。他是IEEE、IET、CACS、RST和TFSA的会士。