Wissenschaftliche/r Mitarbeiter/in im Bereich "Model predictive control of cooperative robot manipulators" (m/w/d)
About us
The chair of Prof. Bajcinca focuses on research of modern methods and advanced applications of control and system theory, involving three main pillars: cyber-physical systems, complex dynamical systems and machine learning. Through networking with a large number of national and international research, academic and industrial partners, funding projects with exotic and highly interesting tasks regarding model-based and data-driven control have been acquired on a regular basis. The research work is supported with an excellent laboratory equipment and high-performance computation in the areas of autonomous systems, robotics and energy systems, which is continuously being further developed.
https://www.mv.uni-kl.de/mec/home.
Research Framework
The efficient deployment of multiple cooperating robotic manipulators in challenging industrial applications brings the promise of shorter processing and task execution times. Usually, in such settings, robots communicate with each other, share sensor information, and coordinate their motions to perform the assigned tasks jointly. However, this can result in robots working close to each other with high overlapping operation areas, which leads to challenging robot motions with high collision potential. This poses new challenges to task and trajectory planning, especially when considering online planning methods. For an efficient and safe robot deployment, prediction-based methods are introduced following a hierarchical control scheme with two optimization-based control policies, a discrete one for task scheduling and a continuous one for trajectory planning.
Task Description
Ongoing research activities on cooperative control of robot manipulators include the following:
- The development of optimization-based algorithms for cooperative robot task planning
- The development of predictive-based algorithms for planning collision-free trajectories for cooperating robotic manipulators in confined working environments
- Optimization-based motion coordination of robotic arms with an omnidirectional mobile robot as part of a dual-armed mobile robotic system
- Coupling of the planning algorithms with computer vision
- Algorithm Implementation on robot manipulators (UR5 from Universal Robots) and mobile robots using ROS (Robot Operating System)
Qualification
- Above average university degree in the field of control engineering, electrical engineering, computer science of mathematics
- Strong analytical and problem-solving skills to address complex issues related to robotic systems
- Advanced knowledge in control engineering and optimization
- Knowledge of at least one programming language: Matlab, Python, C++
- Knowledge in modeling, analyzing, implementing and solving optimization problems
- ROS (Robot Operating System) knowledge is of advantage
- Organizational and cooperation skills with scientific as well as industrial partners of different disciplines
- Proficiency in English or / and German is essential
We offer
- Payment according to TV-L E13 with an initial one-year time limit
- The possibility to do a PhD and to teach is given in case of scientific aptitude
- TUK strongly encourages qualified female academics to apply
- Severely disabled persons will be given preference in the case of appropriate suitability (please enclose proof)
- Electronic application is preferred. Please attach only one coherent PDF.
You can expect an interesting, diversified and responsible task within a young, highly motivated and interdisciplinary team of a growing chair with great personal creativity freedom.
Contact
Prof. Dr.-Ing. Naim Bajcinca
Phone: +49 (0)631/205-3230
Mobile: +49 (0)172/614-8209
Fax: +49 (0)631/205-4201
Email: mec-apps(at)mv.uni-kl.de
Keywords
Predictive control
Trajectory planning
Cooperative robots
Application Papers
Cover Letter
CV
University Certificates
References
List of Publications
Application Deadline
15. April 2024
We will process your application as soon as received.
Job Availability
Immediate