Robin Verschueren

Papers

Total Citations

124

H-Index

About

Robin Verschueren is a leading researcher at the intersection of optimization-based control and robotics, with a focus on making advanced algorithms practical for real-time, embedded systems. His work centers on nonlinear model predictive control (NMPC) and time-optimal motion planning, where he has developed innovative reformulations that bridge the gap between theoretical optimality and computational feasibility. His most cited paper, "Embedded Optimization Methods for Industrial Automatic Control" (2017, 62 citations), provides a comprehensive framework for deploying optimization-based control in industrial settings, building on decades of success in petrochemical and process industries. In robotics, his contributions are equally impactful: his work on "Time-optimal motion planning for n-DOF robot manipulators using a path-parametric system reformulation" (2016, 32 citations) introduces a method that allows small deviations from predefined paths to significantly reduce motion time, while his "Path-following NMPC for serial-link robot manipulators" (2016, 30 citations) balances tracking accuracy with speed. Together, these works have shaped modern approaches to autonomous manipulation and embedded control, earning him recognition as a key figure in making optimization-based methods viable for industrial and robotic applications.