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About

Shubo Liu is a robotics researcher whose work focuses on the motion control and trajectory planning of industrial robotic systems. His key contributions lie in developing advanced control strategies to enhance the precision and robustness of robot manipulators, particularly when dealing with complex nonlinearities and uncertainties. Liu’s most influential work, “An optimal trajectory planning method for path tracking of industrial robots” (2018), has garnered 31 citations and addresses the critical challenge of planning optimal trajectories along specified geometric paths for industrial applications. He has further advanced the field with his research on adaptive sliding tracking control for nonlinear uncertain robotic systems, tackling the difficult problem of unknown actuator nonlinearities. Notably, his 2025 publication in this area introduces a “non-fragile” approach that accounts for controller perturbations, demonstrating his commitment to developing practical, resilient solutions. Liu has also contributed a comprehensive review on the progress and development trends of industrial robot motion control. With a growing body of work that bridges theoretical control design with real-world robotic challenges, Shubo Liu’s research is essential reading for students and engineers working to improve the autonomy and reliability of industrial robots.