/Oliver Kroemer

Oliver Kroemer

Portrait of Oliver Kroemer
Assistant Professor
Office: 4531 Newell-Simon Hall
Administrative Assistant: Ashley Song

Mailing Address

My research focuses on developing algorithms and representations to enable robots to learn versatile manipulation skills over time. The ability to learn skills and adapt manipulations to new situations will open up a wide range of new robot applications, including taking care of the elderly, maintaining parks and public places, and assisting in hazardous environments. I have developed methods for robots to learn about objects through physical interactions and improve their skills autonomously using reinforcement learning. I have also proposed representations for capturing various aspects of manipulations, e.g., contact states and motor primitives, to improve generalization between different scenarios and skills.  The ultimate goal of my research is to develop a life-long learning framework for robots to acquire manipulation skills.

Before joining the CMU Robotics Institute in 2018, I was a postdoctoral researcher at the University of Southern California (USC). I received my Masters and Bachelors degrees in engineering from the University of Cambridge in 2008.  From 2009 to 2011, I  was a Ph.D. student at the Max Planck Institute for Intelligent Systems. In 2014, I defended my Ph.D. thesis at the Technische Universitaet Darmstadt and was a finalist for the 2015 Georges Giralt Ph.D. Award for the best robotics Ph.D. thesis in Europe.

Displaying 7 Publications
Learning Motor Skills – From Algorithms to Robot Experiments
Kober, J., Muelling, K., Kroemer, O., Lampert, C.H., Schoelkopf, B. and Peters, J.

Book Section/Chapter, Chapter: Movement Templates for Learning of Hitting and Batting, Springer Tracts in Advanced Robotics, Vol. 97, January, 2014
Towards Robot Skill Learning: From Simple Skills to Table Tennis
Peters, J., Kober, J., Muelling, K., Kroemer, O. and Neumann, G.

Conference Paper, Proceedings of the European Conference on Machine Learning (ECML), Nectar Track, September, 2013
Learning to Select and Generalize Striking Movements in Robot Table Tennis
Muelling, K., Kober, J., Kroemer, O. and Peters, J.

Journal Article, International Journal of Robotics Research (IJRR), Vol. 32, No. 3, pp. 263 - 279, March, 2013
Learning to Select and Generalize Striking Movements in Robot Table Tennis
Muelling, K., Kober, J., Kroemer, O. and Peters, J.

Conference Paper, Proceedings of the AAAI Fall Symposium on Robots that Learn Interactively from Human Teachers, October, 2012
Robot Skill Learning
Peters, J., Kober, J., Muelling, K., Nguyen-Tuong, D. and Kroemer, O.

Conference Paper, Proceedings of the European Conference on Artificial Intelligence (ECAI), August, 2012
Movement Templates for Learning of Hitting and Batting
Kober, J., Muelling, K., Kroemer, O., Lampert, C.H., Schoelkopf, B. and Peters, J.

Conference Paper, IEEE International Conference on Robotics and Automation (ICRA), April, 2010
Towards Motor Skill Learning for Robotics
Peters, J., Muelling, K., Kober, J., Nguyen-Tuong, D. and Kroemer, O.

Conference Paper, Proceedings of the International Symposium on Robotics Research (ISRR), Invited Paper., August, 2009
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