Joris Gillis
Papers
14
Total Citations
3,784
H-Index
5
About
Joris Gillis is a computational engineer and robotics researcher whose work sits at the intersection of numerical optimization, optimal control, and robot motion planning. He is perhaps best known as a key contributor to CasADi, the influential open-source software framework for nonlinear optimization and optimal control that has amassed nearly 3,700 citations since 2018, making it one of the most widely adopted tools in the optimization and control community worldwide. Beyond CasADi, Gillis has made substantial contributions to nonlinear model predictive control (NMPC) for robot manipulators, developing techniques such as tunnel-following NMPC, which elegantly exploits permissible deviations around path references through convex-over-nonlinear problem structures. His research also advances real-time feasibility of NMPC by leveraging first-order solvers, mixed analytical and algorithmic differentiation strategies, and task-level parallelism to dramatically reduce computation times. He developed Tasho, an open-source Python toolbox enabling rapid prototyping of OCP-based robot motion skills, lowering the barrier for researchers and practitioners alike. His work extends further into environment-aware manipulation planning, web-based robot programming interfaces, and robust time-optimal motion planning for autonomous mobile robots under disturbance. Collectively, Gillis's research equips the robotics and control community with powerful, practical computational tools that bridge sophisticated mathematical theory and real-world deployment.
Research Focus
Key Achievements
Top Papers
- 1CasADi: a software framework for nonlinear optimization and optimal control3,693 citations · 2018
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