PHD POSITION IN FAST OPTIMAL MOTION PLANNING FOR ROBOT GRIPPING ACTIONS

BAP-2020-567

13 July 2020

Apply before 30 September 2020

The Robotics, Automation and Mechatronics (RAM) division of the Department of Mechanical Engineering is looking for a doctoral researcher to join the MECO research team.

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Project

The Industry 4.0 transformation is characterized by mass customization of products and advanced automation needs. As the context of an assembly or machining action moves from fixed to ever-changing, there arises a pressing need for strategies to plan robot motion on-the-fly, as opposed to classic pre-programmed motions. Current state-of-the art motion planners are lacking in optimality (do we find the fastest possible motion plan?), in computational speed (can we avoid dead-time of the system?), or in robustness (do we have a high success rate?).

In the Flemish FROGS (Flexible and Robust Robotics Gripping) project, several Flemish universities and companies join forces to design a holistic architecture to solve the robot gripping problem. In this context, KU Leuven will focus on the motion planning aspects.

In this research you will contribute to the development, implementation and experimental validation of a novel motion planning framework. This framework is proactive: it exploits a geometric and kinematic model of the robot to predict the outcome of control actions, allowing to produce those control trajectories up-front that lead to a collision free trajectory that obeys pose-to-pose boundary conditions and is optimal with respect to a chosen objective. Gradient-based constraint optimization techniques are central to the implementation. Your focus will be on identifying problem formulations that lead to fast computations with limited loss of optimality. Examples of possible formulations include a smart low-dimensional parametrization of the sought trajectory, a subdivision in geometric path generation and trajectory generation, and subdivision between offline optimization and online optimization. You will cooperate with the other researchers involved in this project in order to demonstrate your techniques on industrially relevant setups.

You will be embedded in the MECO (Motion Estimation Control and Optimization) research team of the KU Leuven Department Mechanical Engineering. The MECO team focusses on the identification, analysis and control of mechatronic systems such as autonomous guided vehicles, robots, and machine tools. It combines theoretical innovations with experimental validations. The theoretical research benefits from the team’s expertise on numerical optimization, while MECO’s practical knowhow and industrial collaboration are supported by its participation in Flanders Make – the Flemish strategic research center for the manufacturing industry.

Profile

Ideal candidates hold a Master’s degree in engineering, computer science, or applied mathematics. Successful candidates are typically ranked at or near the top of their classes, have a solid background in systems and control, robotics, optimization, relevant computer programming skills (Python or Matlab, C++), and enthusiasm for scientific research, including real-hardware implementations and experiments. 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).
Offer

A fully funded PhD position in an international context for four years at KU Leuven: a top European university and a hub for interdisciplinary research in the fields of systems, control and optimization. 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 2020 or early 2021 is to be agreed upon.

Interested?

Please use the online application tool to submit your application and include:

[1] an academic CV with photo;

[2] a PdF of your diplomas and transcripts of course work and grades;

[3] statement of research interests and caeer goals (max. 2 pages);

[4] sample of technical writing (publication or thesis);

[5] contact details of at least two referees;

[6] proof of English language proficiency test results.

For more information please mail: meco.hr@kuleuven.be

You can apply for this job no later than September 30, 2020 via the online application toolKU 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 diversiteit.HR@kuleuven.be.