Fast Model Predictive Control for Robots
The KU Leuven, Department of Mechanical Engineering is searching for a young, motivated and skilled PhD researcher with a strong background in numerical optimization, systems and control, and robotics. This research will be performed in the MECO research team (Motion Estimation Control and Optimization), of the department Mechanical Engineering, KU Leuven.
MECO is involved in the KU Leuven Center of Excellence on Optimization in Engineering (OPTEC), is a strategic partner of Flanders Make, and has a close cooperation with leading mechatronic and machine-building companies in Flanders. The MECO research team focusses on modeling, estimation, identification, analysis and optimal control of motion and motion systems such as mechatronic systems, machine tools. It combines theoretical contributions (development of design methodologies) with experimental knowhow (implementation and experimental validation on lab-scale as well as industrial setups). The theoretical research benefits from the group's expertise on numerical optimization, especially convex optimization.
This project focuses on optimal contact-free motion control of serial robots operating in changing environments. Changing environments require real-time motion planning, which is very challenging due to complex robot kinematics and dynamics and continuously changing collision constraints. The overall project goal is to develop and experimentally validate an effective MPC approach for serial robots that realizes contact-free optimal robot motion planning and control in real-time. This research will be supported by an MPC toolchain development in order to integrate all software in an open and modular fashion as to create a workflow from problem specification to deployment. All developments will be validated experimentally on industrial robotic set-ups in the lab.
This job comes from a partnership with Science Magazine and