Jens Kober Member
Jens Kober
Jens Kober joined the Max-Planck Institute for Intelligent Systems in 2007 as a Master's Student in the Department of Bernhard Schölkopf under the supervision of Jan Peters. Before doing so, he studied at the University of Stuttgart and at the Ecole Centrale Paris (ECP).
In 2008 he completed the double degree program T.I.M.E. and graduated from the University of Stuttgart with a Diplom-Ingenieur in Engineering Cybernetics (German M.Sc. majoring in automation & control) as well as from ECP as a Centralien (French engineering degree with an integrated multidisciplinary approach). He has been a visiting research student at the Advanded Telecommunication Research (ATR) Center in Japan and an intern at Disney Research Pittsburgh, USA. Please see his curriculum vitae for more biographical information.
Jens Kober is currently working towards a Ph.D. in the area of motor skill learning with a strong focus on learning motor primitives and on reinforcement learning. He is an external Ph.D. students at Technische Universität Darmstadt. Jens Kober is a teaching assistant of the Projektpraktikum: Lernende Roboter.
Integrating highly complex robots in daily life requires them to become more independent of preprogrammed behaviors and exception handling. As biological research has shown different complex movements are actually a result of the combination of simple motor primitives. This concept is also successfully applied to robotics but there remains still a lot of research to be done in order to make the current formulations more versatile. In nature as in robotics tasks are often learned by observation and imitation. In many cases the imitation is imperfect and has to be improved. Reinforcement Learning is a natural choice for this step.
Jens Kober can be found on [Google Citations] and [DBLP].
Research Interests: Robotics, Machine Learning
Biographical Information: Please see his curriculum vitae.
Publications: For the complete list of his publication, see here.
Collaborators: Betty Mohler, Silvia Chiappa, Katharina Muelling, Oliver Kroemer, Christoph Lampert, Bernhard Schölkopf, Erhan Oztop, Jan Peters.
Software
A basic MATLAB/Octave implementation of the PoWER algorithm [1]: matlab_PoWER.zip
The required motor primitive code can be downloaded from
http://www-clmc.usc.edu/Resources/Software.
A basic MATLAB/Octave implementation of the motor primitives for hitting and batting [4]: hittingMP.m
Key References
- Kober, J.; Peters, J. (2009). Policy Search for Motor Primitives in Robotics, Advances in Neural Information Processing Systems 22 (NIPS 2008), Cambridge, MA: MIT Press download with a longer version in
Kober, J.; Peters, J. (2011). Policy Search for Motor Primitives in Robotics, Machine Learning, 84, 1-2, pp.171-203 download - Kober, J.; Peters, J. (2009). Learning Motor Primitives for Robotics, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) download with a longer version in
Kober, J.; Peters, J. (2010). Imitation and Reinforcement Learning - Practical Algorithms for Motor Primitive Learning in Robotics, IEEE Robotics and Automation Magazine, 17, 2, pp.55-62 download - Chiappa, S.; Kober, J.; Peters, J. (2009). Using Bayesian Dynamical Systems for Motion Template Libraries, Advances in Neural Information Processing Systems 22 (NIPS 2008), Cambridge, MA: MIT Press download
- Kober,J.; Muelling,K.; Kroemer, O.; Lampert,C.H.; Schoelkopf, B.; Peters, J. (2010). Movement Templates for Learning of Hitting and Batting, IEEE International Conference on Robotics and Automation (ICRA) download
- Kober, J.; Oztop, E.; Peters, J. (2010). Reinforcement Learning to adjust Robot Movements to New Situations, Proceedings of Robotics: Science and Systems (R:SS) download
Contact Information
Mail: Jens Kober, AGBS, Spemannstr. 38, 72076 Tübingen, Germany
+49-7071-601-548
+49-7071-601-552
jens.kober@tuebingen.mpg.de
