Rudolf Lioutikov

Assistant Professor of Practice, College of Natural Sciences
Rudolf Lioutikov joined the Intelligent Autonomous System lab on November 1, 2013 as a Ph.D. student. His research includes imitation-learning, skill learning, motion segmentation and human-robot interaction for non-experts. During his Ph.D., Rudolf worked on the 3rd Hand Project where he developed and evaluated new approaches in the field of semi-autonomous human-robot collaboration tasks. Combined, the developed methods form an imitation learning pipeline.


Research Interests: 
  • Imitation Learning
  • Reinforcement Learning
  • Policy Search
  • Movement Primitive Representation
  • Skill Acquisition
  • Movement Segmentation
  • Structure Learning
  • Grammar Induction
  • Skill Composition and Sequencing Life-Long and Active Learning

Select Publications

Maeda, G.; Neumann, G.; Ewerton, M.; Lioutikov, R.; Kroemer, O.; Peters, J.. 2017. Probabilistic Movement Primitives for Coordination of Multiple Human-Robot Collaborative Tasks.
Maeda, G.; Ewerton, M.; Neumann, G.; Lioutikov, R.; Peters, J.. 2017. Phase Estimation for Fast Action Recognition and Trajectory Generation in Human-Robot Collaboration.
Osa, T.; Ghalamzan, E. A. M.; Stolkin, R.; Lioutikov, R.; Peters, J.; Neumann, G.. 2017. Guiding Trajectory Optimization by Demonstrated Distributions.
Lioutikov, R.; Neumann, G.; Maeda, G.; Peters, J. . 2017. Learning Movement Primitive Libraries through Probabilistic Segmentation.
Paraschos, A.; Lioutikov, R.; Peters, J.; Neumann, G.. 2017. Probabilistic Prioritization of Movement Primitives.