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KU Leuven
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B-SPLINE BASED MOTION PLANNING AND MODEL PREDICTIVE CONTROL

(Ref. BAP-2017-150)
Occupation: Full-time
Period: Fixed-term contract
Place: Leuven
Apply no later than: April 30, 2017
For the Production Engineering, Machine Design and Automation (PMA) Section we are looking for a young, motivated and skilled PhD researcher with a strong background in numerical optimization, systems theory and control.
For the Production Engineering, Machine Design and Automation (PMA) Section we are looking for a young, motivated and skilled PhD researcher with a strong background in numerical optimization, systems theory and control.
B-SPLINE BASED MOTION PLANNING AND MODEL PREDICTIVE CONTROL
You will be embedded in the MECO research team of the KU Leuven Department of Mechanical Engineering. The MECO research team focusses on the identifi­cation, analysis and control of mechatronic systems such as machine tools, active suspensions, robots... Herein theoretical developments are combined with experimental validations on lab-scale as well as industrial setups.
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Project
In motion planning one seeks for the fastest, most energy efficient... trajectory to move a motion system from its current position to its destination, while accounting for the system’s kinematic and dynamic constraints and avoiding collisions with all obstacles in the environment. It plays a vital role in the control of autonomous guided vehicles, CNC machine tools, serial robots. As motion planning is often performed on line, in a model predictive control fashion, solving the resulting optimization problems efficiently and reliably is of the utmost importance. Recently, we have developed an effective motion planning method based on B-splines. The motion trajectory is parameterized as a polynomial spline and the properties of the B-spline basis functions are exploited to efficiently enforce constraints over the considered time horizon. The method is implemented in the open source Python toolbox OMGtools (https://github.com/meco-group/omg-tools). In this research project you will extend this motion planning approach to a broad range of systems, and in collaboration with experts in numerical optimization, you will supply it with tailored optimization routines. In addition, you will contribute to the underlying B-spline based optimization approaches and explore additional uses of these approaches in model predictive control.
Profile
An ideal candidate holds a degree in engineering, computer science, or applied mathematics. He or she has a solid background in numerical optimization, systems theory and control, a strong interest and experience in mathematical programming (Matlab, Python, C/C++), and enthusiasm for scientific research. Team player mentality, independence, and problem solving skills are expected, and proficiency in English is a requirement.
Offer
A fully funded PhD position for four years at the KU Leuven (more information for PhD students at the KU Leuven is found at https://www.kuleuven.be/personeel/jobsite/en/phd-info). KU Leuven is among the top European universities and a hub for interdisciplinary research in the field of control and optimization. You will be embedded in the MECO research team of the department of Mechanical Engineering (https://www.mech.kuleuven.be/en/pma/research/meco). The MECO research team focusses on the identification, analysis and control of mechatronic systems such as machine tools, active suspensions, robots... Herein theoretical developments are combined with experimental validations on lab-scale as well as industrial setups.
A starting date in the course of 2017 is to be agreed upon.
Interested?
For more information please contact Prof. dr. ir. Goele Pipeleers, tel.: +32 16 37 26 94, mail: goele.pipeleers@kuleuven.be.
Applications should include:
* an academic CV
* 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, in case your mother to.ngue is neither Dutch nor English
You can apply for this job no later than April 30, 2017 via the
online application tool

Closing date: 30.04.2017
Closing date: 30 April 2017 Erschienen auf academics.de am 15.03.2017
In your application, please refer to academics.com