Max Robotics — Global Service Robot Directory + US Certification

About

Yueshi Shen is a robotics researcher whose work centers on robot motion planning, trajectory optimization, and compliant motion control for manipulator systems. His most significant contributions lie in developing mathematically rigorous methods for solving complex robot control problems that arise when robotic arms interact with constrained environments. Shen's most impactful work focuses on optimal joint trajectory planning for manipulator robots performing constrained and compliant motion tasks. His novel two-step scheme, which approximates complex functionals and applies Newton's iteration to avoid intractable nonlinear Euler-Lagrange equations, has attracted 18 citations and represents a practical advance in making trajectory optimization computationally feasible. Complementing this, his research on smooth interpolation of orientations using rolling and wrapping on the rotation group SO(3) — cited 15 times — offers elegant geometric solutions for representing rigid-body motion in robot path planning. Beyond trajectory planning, Shen has contributed to hybrid motion/force control through joint space formulations designed to improve robustness in both constrained and redundant robot configurations. His early investigation into ill-conditioned inertia matrices further demonstrates his attention to real-world control stability challenges. Collectively, his research provides both theoretical foundations and practical tools that continue to inform the design and control of modern robotic manipulators.