"Artificial Intelligence for Machine Tools and Robotics"

Organizers:

Xuesong Mei, Xi’an Jiaotong University, China

Professor Xuesong Mei is a Changjiang Scholar Distinguished Professor and the leader of an Innovation Team of the Ministry of Education. He has long been engaged in theoretical research, technology development, and engineering applications for high-end CNC equipment. He has achieved systematic innovations in both theory and practice, particularly in multi-axis motion control for advanced manufacturing equipment, error control of high-grade CNC machine tools, and multi-field regulation in ultrafast laser processing. His work has addressed key manufacturing challenges in high-end CNC manufacturing equipment and in aerospace and other strategic sectors.
He has published over 500 journal papers and has been granted more than 300 invention patents. His achievements have received three Second Prizes of the National Science and Technology Progress Award and one First Prize of the Shaanxi Provincial Technological Invention Award. His contributions to education and research in intelligent manufacturing have also been recognized with two Second Prizes of the National Teaching Achievement Award. He has served as editor-in-chief of six monographs and textbooks, including Pulsed Laser Processing Technology and Machine Tool CNC Systems.

Gedong Jiang, Xi’an Jiaotong University, China

Gedong Jiang received the Ph.D. degree in mechanical engineering from the Xi’an Jiaotong University, Xi’an, China, in 1998. She is currently a Professor with the School of Mechanical Engineering, Xi’an Jiaotong University. She is a recipient of the Ministry of Education’s New Century Excellent Talents program and serves as the chief scientist of a National Key R&D Program project. Her research interests include smart manufacturing, condition monitoring, and robotics.

Jun Xu, Xi’an Jiaotong University, China

Jun Xu is currently a professor and a Ph.D. supervisor with School of Mechanical Engineering, Xi'an Jiaotong University. He is the director of the Digital Energy Research Institute, and the director of the Energy Storage and Inverter Institute. He serves as IAAM Fellow, IEEE Senior Member, the Vice Chairman of Shaanxi Power Supply Society, the Chairman of Youth Working Committee of SAE-Shaanxi, the Associate Editor of journals, and Conference Chair/Conference Co-Chair of Academic Conferences, etc. His research interests include design, modeling, and control of battery systems, electric vehicles, renewable energy systems, and robots.

Hanbo Yang, Xi’an Jiaotong University, China

Hanbo Yang is an Assistant Professor at Xi’an Jiaotong University. From 2021 to 2022, he was sponsored by the China Scholarship Council (CSC) to conduct research as a visiting Ph.D. student at the National University of Singapore (NUS). He obtained his Ph.D. in Mechanical Engineering from Xi’an Jiaotong University in 2023. His research interests include cyber-physical systems for smart manufacturing, CNC machining technology, Industrial Internet technologies, and industrial software systems.

Introcduction:

Industrial machine tools and industrial robots are foundational to high-end manufacturing. However, their performance is increasingly constrained by complex and time-varying factors, including thermo-mechanical coupling, tool–workpiece interaction uncertainties, degradation, and changing production contexts. Meanwhile, factories are rapidly adopting Industrial Internet infrastructures, enabling large-scale sensing, connectivity, and heterogeneous data acquisition across equipment and processes. This convergence creates a timely opportunity to advance manufacturing intelligence through artificial intelligence (AI), including machine learning, foundation models, and physics-informed approaches.
This Special Session focuses on how AI can be systematically integrated into machine tools and robotics to improve accuracy, productivity, robustness, and autonomy, with a strong emphasis on industrial deployability and real-world validation. Topics of interest include (i) high-precision modeling, control, and error compensation for CNC machine tools and robotic systems; (ii) Industrial Internet of Things (IIoT)–enabled smart manufacturing systems; and (iii) embodied intelligence for perception, decision-making, and adaptive motion planning in manufacturing scenarios. In addition, we encourage contributions on digital-twin-enabled learning and online model updating under non-stationary environments, interoperability with industrial protocols.
By bringing together researchers and practitioners from machine tool engineering, robotics, industrial informatics, and AI, this session aims to foster cross-disciplinary methodologies and accelerate the translation of AI innovations into measurable manufacturing impact.

Conference Track(s)

• High-Precision Control for CNC Machine Tools and Robotics

• Digital Twin, Industrial Informatics, and Industrial Internet (IIoT)

• Embodied Intelligence and Robotics