Yuchen Lu

University of Toronto, Beijing Institute of Technology

Papers

Total Citations

215

H-Index

About

Yuchen Lu is a leading researcher at the intersection of robotics and control theory, with key contributions in robotic manipulation and model predictive control (MPC). Lu’s work on deformable object manipulation, particularly in the context of biological cells, has been highly influential. Their 2019 paper on robotic orientation control of deformable cells (86 citations) addresses the unique challenge of handling highly deformable, damage-prone biological materials, advancing the field of medical robotics and cell manipulation. In control systems, Lu has made significant strides in robust MPC. Their 2021 paper on disturbance rejection MPC for input-affine nonlinear systems (80 citations) introduces a novel framework that enhances robustness against state-dependent disturbances, a critical advancement for real-world applications. Complementing this, their 2020 work on robust tracking MPC for mobile robots (49 citations) incorporates quadratic robustness constraints and incremental input constraints to ensure safety and stability under bounded disturbances. With over 215 citations across these core papers, Lu’s research is shaping safer, more reliable autonomous systems, from surgical robotics to mobile robot navigation.