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    绣山讲坛第393讲-Structural Innovation Towards Intelligent Robotics: (6+3)-DOF Parallel Robots with Very Large Rotational Workspace

    发布日期:2025-09-03 文章来源:机械工程与力学学院

    ​报告题目:Structural Innovation Towards Intelligent Robotics: (6+3)-DOF Parallel Robots with Very Large Rotational Workspace 报告时间:2025年8月8日 9:00 报告地点:绣山工程楼208会议室 主讲人:Dr. Kefei Wen (温科飞),Assistant Professor,Department of Mechanical Engineering,The University of British Columbia 摘要: Parallel robots offer higher speed and payload capacity than their serial counterparts, but their industrial adoption is hindered by limited rotational capability caused by internal singularities. In this talk, we introduce a new class of kinematically redundant (6+3)-DOF parallel robots that fully eliminate singularities and achieve an unprecedented very large rotational workspace. This structural innovation makes them strong candidates for advanced manufacturing and human-robot collaboration. Beyond their mechanical advantages, these robots also provide a promising platform for future integration with data-driven control, intelligent motion planning, and real-time sensor fusion-positioning them at the intersection of robotics and information technologies. 主讲人简介: Kefei Wen is an Assistant Professor with the Department of Mechanical Engineering at the University of British Columbia, Canada. He received the B.S. and M.S. degrees in Mechanical Engineering from Yeungnam University, South Korea, and the Ph.D. degree in Mechanical Engineering from Université Laval, Québec, Canada. During his Ph.D. studies, he developed a methodology for synthesising novel kinematically redundant parallel manipulators which are well-suited for physical human-robot interaction. He was a Postdoctoral Fellow in the Continuum Robotics Laboratory at the University of Toronto, where he proposed a scheme to unify the modelling approaches of both rigid parallel robots and tendon-driven parallel continuum robots. His research interests include kinematics, dynamics, and control of complex robotic systems. Dr. Wen received the ASME JMR 2020 Reviewers of the Year Award and a Best Paper Honorable Mention at IEEE T-RO 2021.

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