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Professor ZHANG Dan
PolyU Scholars Hub

Professor ZHANG Dan

Director, PolyU-Nanjing Technology and Innovation Research Institute
Director, Consortium for Intelligent Robotics Research
Chair Professor of Intelligent Robotics and Automation

  • Fellow of the Canadian Academy of Engineering
  • Fellow of the Engineering Institute of Canada
  • Fellow of the American Society of Mechanical Engineers
  • Fellow of the Canadian Society for Mechanical Engineering

 

Professor Zhang Dan is a well-accomplished educator and an internationally renowned expert in the areas of parallel robotic machines and their applications in manufacturing systems. His influential scientific contributions have led to novel robotic system designs and the development of new comprehensive models for a better understanding of globe stiffness and robotic calibrations. His research applications have tackled some of the world's most challenging problems in high dynamic performance manufacturing robotic systems. His innovative calibration method, which employs pseudo-error theory and a cooperative co-evolutionary neural network, has revolutionised the calibration of robotic systems by providing a rapid and precise means to account for the cumulative effect of various error sources. His comprehensive model of hinge installation error, lead screw execution error, and random error, along with the compensation technique, has not only been effectively applied in high-precision three-axis parallel robotics machine tools but was also adopted in the study of the 50m model of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). This technology significantly improved the execution precision of the feed source fine-tuning platform, achieving sub-millimeter level positioning accuracy, which allowed FAST to strive for even greater precision.

His exceptional contributions have been celebrated with numerous accolades, including the Canada Research Chair, Research Excellence Awards, the Tier 1 York Research Chair, Lassonde Innovation Awards for Established Researchers, and the Early Researcher Award from the Ministry of Research and Innovation of Ontario. He has also held fellowships with the Canadian Academy of Engineering (CAE), the Engineering Institute of Canada (EIC), the American Society of Mechanical Engineers (ASME), and the Canadian Society for Mechanical Engineering (CSME), underscoring his significant contributions to engineering and research.

Professor Zhang's dual appointments as a Canada Research Chair in Advanced Robotics and Automation underscore his leadership and innovation in the field. The Early Researcher Award from the Province of Ontario, along with his roles as the Kaneff Professor and Tier 1 York Research Chair in Advanced Robotics and Mechatronics at York University, highlight his outstanding global reputation and contributions to his areas of specialisation.

His seminal contributions to Parallel Kinematic Machines (PKM) have been instrumental in advancing computational control for machining applications, as elaborated in his publication "Parallel Robotic Machine Tools." Professor Zhang's pioneering work in modelling manipulator stiffness, with an emphasis on flexible links and joints, has facilitated real-time control and the prediction of system stiffness, marking a significant milestone in the field. Beyond the confines of academia, Professor Zhang has translated his research into tangible innovations, securing over 40 Chinese patents and contributing to national standards. His inventions, including a PKM for precision machining and a bio-inspired robot designed for mine rescue operations, underscore his dedication to leveraging his expertise to address real-world challenges. Professor Zhang's distinguished record of research, leadership, and mentorship has not only propelled academic and industrial R&D programs to new heights in the field of robotics but has also left an indelible mark on the global stage. His visionary work continues to inspire and catalyse innovation in robotic technology and its diverse applications, shaping the future of the field.

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