LI, Xiang


Associate Professor

Department of Automation, Tsinghua University

Beijing, China

Email: xiangli@tsinghua.edu.cn 

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Xiang LI received the Bachelor and Master degrees from Beijing Institute of Technology in 2006 and 2008, and the PhD degree from Nanyang Technological University in 2013 respectively. From Aug. 2012 to Feb. 2015, he was a Research Fellow at the Intelligent Robotics Lab, Nanyang Technological University, Singapore. From Feb. 2015 to Aug. 2016, he was a Research Fellow at the Department of Biomedical Engineering, National University of Singapore. From Aug. 2016 to Aug. 2019, he was a Research Assistant Professor at the Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong. He is now working as an Associate Professor at the Department of Automation, Tsinghua University.

Xiang LI was the Associate Editor of IEEE Robotics & Automation Magazine from 2019 to 2021 and the Associate Editor of IEEE International Conference on Robotics and Automation (ICRA) from 2019 to 2021. He has been the Associate Editor of IEEE Robotics and Automation Letters since 2022, and the Associate Editor of IEEE Transactions on Automation Science and Engineering since 2023. He received the Highly Commended Paper Award in 2013 IFToMM International Symposium on Robotics and Mechatronics, the Best Paper in Robotic Control in 2017 International Conference on Advanced Robotics, the Best Application Paper Finalists in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), and the T. J. Tarn Best Paper in Robotics in IEEE International Conference on Robotics and Biomimetics. He is the Program Chair of the 2023 IEEE International Conference on Real-time Computing and Robotics.  His current research interests include deformable object manipulation, physical human-robot interaction, robot-assisted optical tweezers, and multi-agent system.

Research Highlights

Robot Control: Proposed a global task-space robot controller to deal with limited sensing zone and singularity in robot task space control; Proposed a dynamic region control approach with guaranteed transient and steady-state performance.

Robot-Assisted Optical Manipulation: Reported the first result on dynamic trapping and manipulation of biological cells with optical tweezers, and addressed the problem of local effectiveness of existing methods; Developed robotic techniques for optical manipulation with unknown trapping stiffness, limited FOV, and Brownian motions.

Physical Human-Robot Interaction: Developed a theoretical framework to integrate multiple interaction modes into a single controller and take advantages of both human knowledge and robot's ability in a stable and smooth manner; Successfully implemented it in lower-limb exoskeleton and validated in clinical trials.

Deformable Object Manipulation: Proposed a coupled offline and online data-driven method for efficiently learning a global deformation model of deformable linear objects; Applied to vision-based robotic manipulation of flexible PCBs and USB wires in 3C manufacturing.


Updated on 21 July 2023