PhD Position on Motion Planning and Optimal Control of Multi-Robot Systems KU Leuven, Leuven Production Engineering, Machine Design and Automation (PMA) Section Belgium


You will be embedded in the MECO (Motion Estimation Control and Optimization) research team of the KU Leuven Department of Mechanical Engineering. The MECO research team focusses on identification, analysis and optimal control of mechatronic systems such as autonomous guided vehicles, robots, and 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. MECO is member of Flanders Make - the strategic research centre for the manufacturing industry.



To address the increasing demand for flexible automation, robot manufacturers invest strongly in new technologies and have presented two-armed robots and mobile manipulator systems to the market. These novel robotic solutions open up disruptive possibilities for the realization of effective, flexible manufacturing systems. In many applications, multi-robot solutions are superior to single-robot solutions because of the higher level of flexibility and dexterity that they can offer, which are characteristics needed to raise the level of automation of current industrial solutions. Although multi-robot systems have generated a “buzz” in robotic circles, the real industrial uptake is still limited. A key technological barrier is the difficulty to deploy and use the systems in real-life industrial environments with limited structure using the current state-of-the-art industrial robot programming frameworks. Programming and re-programming these robotic solutions with many degrees of freedom and multiple sensors is a cumbersome and time-consuming task, impeding widespread use.


Your contribution to addressing this technological barrier consists of developing numerically efficient algorithms for solving multi-robot optimal motion planning problems. Solver times within the range of 10 - 100 ms are ambitioned in order to enable re-optimizing the trajectories in real time during task execution. In a second step, you will extend the online trajectory optimization to an effective control approach for sensor-based robot tasks by integrating it with sensing and estimation in order to handle and reduce uncertainty in the environment. The project will involve theoretical innovations as well as implementation of the developed techniques and experimental validations. Several experimental demonstration cases are available for this research: omnidirectional mobile platforms, multiple robotic arms, ...



Ideal candidates hold a Master’s degree in engineering (mechanical, control ...).  Successful candidates have typically ranked at or near the top of their classes, have a solid background in systems, control, robotics, and numerical optimization, relevant computer programming skills, a strong interest and experience in real-world applications, and enthusiasm for scientific research. Team player mentality, independence, and problem solving attitude are expected, and proficiency in English is a requirement.


Applicants whose mother tongue is neither Dutch nor English must present an official language test report. The acceptable tests are TOEFL, IELTS, and Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Required minimum scores are:

  • TOEFL: 600 (paper-based test), 100 (internet-based test)
  • IELTS: 7 (only Academic IELTS test accepted)
  • CAE/CPE: grade B or A


A fully funded PhD position in an international context for four years at the KU Leuven: a top European university and a hub for interdisciplinary research in the fields of systems, control and optimization. You will be embedded in the MECO research team of the Department of Mechanical Engineering. The doctoral candidate will work in world-class facilities with highly qualified experts, and will benefit from the training scheme developed based on the expertise of academic and industrial partners. A start date in the course of 2018 is to be agreed upon.



Please use the online application tool to submit your application. Include: • an academic CV with photo, • a Pdf of your diplomas and transcript of course work and grades, • statement of research interests and career goals (max. 2 pages), • sample of technical writing (publication or thesis), • contact details of at least two referees, • proof of English language proficiency test results. For more information please contact dr. ir. Wilm Decré, mail: Subject of your email should be: "Multi-robot motion planning PhD application".

You can apply for this job no later than June 30, 2018 via the online application tool

KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at

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