Learning Complex Robot-Environment Interactions (Talk)

• Jens Kober ( Associate Professor)

• TU Delft

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I will discuss various learning techniques we developed that can handle complex interactions with the environment. Complexity arises from non-linear dynamics in general and contacts in particular, taking multiple reference frames into account, dealing with high-dimensional input data, etc. I will present our methods on multi-modal imitation learning, the use of models for reinforcement learning in these scenarios, and discuss the particular challenges posed by deep reinforcement learning for these applications. I will illustrate these concepts with benchmark tasks and real robot experiments like pushing objects, unscrewing a lightbulb, or extracting teeth.

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Biography: Jens Kober is an assistant professor at the TU Delft, Netherlands. He worked as a postdoctoral scholar jointly at the CoR-Lab, Bielefeld University, Germany and at the Honda Research Institute Europe, Germany. He graduated in 2012 with a PhD Degree in Engineering from TU Darmstadt. For his research he received the annually awarded Georges Giralt PhD Award for the best PhD thesis in robotics in Europe. From 2007-2012 he was working with Jan Peters as a masters student and subsequently as a PhD student at the Robot Learning Lab, Max Planck Institute for Intelligent Systems (formerly part of the MPI for Biological Cybernetics). He has been a visiting research student at the Advanced Telecommunication Research (ATR) Center, Japan and an intern at Disney Research Pittsburgh, USA. His research interests include robotics, machine learning, and control.