Proceedings of the 3rd International Conference on the Frontiers of Robotics and Software Engineering (FRSE 2025)

This book is a collection of research papers from the 3rd International Conference on the Frontiers of Robotics and Software Engineering (FRSE 2025), featuring contributions from leading experts in the field. It presents innovative research in the fields of robotics and software engineering, showcasing cutting-edge topics such as robot design, industrial automation, human-robot interaction, medical robotics, and advanced algorithms. The proceedings explore developments in cyber robotics, mechatronics systems, and software engineering methods, as well as the integration of virtual environments and augmented reality into robotics applications. By addressing both theoretical advancements and practical applications, the book offers insights into how emerging technologies are shaping the future of robotics and software systems. Readers will benefit from the latest findings and methodologies, and will be inspired to explore new approaches in their own research or industrial work. The primary audience includes academic researchers, engineers, industry professionals, and graduate students involved in robotics, automation, software engineering, and related fields.

Zhao Mingguo received B.E. degree in mechatronic engineering, the M.Sc. degree in space vehicle design, and the Ph.D. degree in mechatronic engineering from Harbin Institute of Technology, Harbin, China, in 1995, 1997, and 2001, respectively. From 2001 to 2003, he was Postdoctoral with the Department of Precision Instrument, Tsinghua University, Beijing, China. In 2014, he was Visiting Scholar with the Massachusetts Institute of Technology, Cambridge, MA, USA. He is currently Professor with the Department of Automation, Tsinghua University. His research interests include the integration of "brain-inspired chips" and "brain-inspired computing" to build a research platform for artificial general intelligence, as well as brain-inspired computing-based robotic control encompassing locomotion, whole-body control, and neuromorphic robotics in humanoid robots.

Jin Zhang is Professor and Doctoral Advisor at Changsha University of Science and Technology (CSUST), where he serves as Dean of the College of Computer and Communication Engineering. He is also Director of the Hunan Provincial Engineering Research Center for Power Blockchain. In the field of scientific research, Prof. Zhang has led over 20 projects, including those funded by the National Natural Science Foundation of China (NSFC). He has published more than 80 research papers in prestigious journals and conferences, including PNAS, and has received the China Industry-Academia-Research Collaboration Innovation Award.

Jiangping Hu received the B.S. degree in applied mathematics and the M.S. degree in computational mathematics from Lanzhou University, Lanzhou, China, in 2000 and 2004, respectively, and the Ph.D. degree in modeling and control of complex systems from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China, in 2007. He has held various positions with the Royal Institute of Technology, Stockholm, Sweden, The City University
of Hong Kong, Hong Kong, Sophia University, Tokyo, Japan, and Western Sydney University, Sydney, NSW, Australia. He is currently a Professor with the School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China. His research focuses on uncertain multi-agent control and optimization. He has published 120 SCI papers in top-tier automation journals including Automatica and IEEE Transactions (81 as first/corresponding author, 19 ESI Highly Cited Papers, with 5,208 SCI citations), authored one monograph, and been granted 10 invention patents. He has led several key projects, including sub-projects of the National Key R&D Program, projects under the National Natural Science Foundation, and the Ministry of Education's New Century Excellent Talents Support Program. The efficient distributed learning control method he proposed addresses online model identification and dynamic control in uncertain multi-agent systems, with related achievements becoming benchmark methods in unmanned swarm decision-making and control. His work has been cited and recognized by 130 IEEE Fellows, and he has received the Automatica Highly Cited Paper Award and the Control Theory and Technology Best Paper Award. He currently serves as an editorial board member for journals such as Journal of Systems & Complexity, Kybernetika, Mathematics, and Plos Complex Systems, and holds roles as General Chair, Publication Chair, or Program Chair for conferences including FRSE 2024,2025, EEAC 2024, ICoCTA 2025, and ICSET 2025. He has been consistently listed in World's Top 2% Scientists and promotes industry-academia-research integration and disciplinary development in intelligent robotics.