Dorothea Koert

Dorothea Koert is the head of the interdisciplinary junior research group IKIDA which started in Oktober 2020 and a postdoctoral researcher at the Intelligent Autonomous Systems Lab.

She has studied Autonomous Systems and Computational Engineering with focus on Robotics in her Master's and successfully defended her Ph.D. thesis "Interactive Machine Learning for Intelligent Assistive Robots" in February 2020 at the Technical University of Darmstadt.

In 2019 she was awarded with the AI-Newcomer award of the German society for Computer Science (GI). During her PhD on 'Interactive Machine Learning for Assistive Robots' she has worked on imitation learning and interactive reinforcement learning, for autonomous and semi-autonomous acquisition of motion skill libraries in human-robot collaboration.

Beside the IKIDA project she is also working on the KOBO project which aims to contribute to improving the social participation of elderly people and maintaining their independence with a humanoid service robot.

Before joining the Autonomous Systems Labs, Dorothea Koert received a Bachelor of Science degree in Computational Engineering (focus on mechanical engineering) and a Master of Science degree in Computational Engineering (focus on computational robotics) as well as a Master of Science degree in Autonomous Systems from the TU Darmstadt. Between 2012 and 2016 she was a member of Team Hector, a robotics team with focus on Search and Rescue robotics, and participated in the RoboCup Rescue League as well as in the Darpa Robotics Challenge and the ARGOS challenge.

Research Interest

Robot Skill Learning, Learning from Demonstrations, Interactive Machine Learning, Human Robot Interaction

Key References

1. Knaust, M.; Koert, D. (2021). Guided Robot Skill Learning: A User-Study on Learning Probabilistic Movement Primitives with Non-Experts, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   BibTeX Reference [BibTex]
2. Koert, D.; Kircher, M.; Salikutluk, V.; D'Eramo, C.; Peters, J. (2020). Multi-Channel Interactive Reinforcement Learning for Sequential Tasks, Frontiers in Robotics and AI Human-Robot Interaction.   Download Article [PDF]   BibTeX Reference [BibTex]
3. Koert, D.; Pajarinen, J.; Schotschneider, A.; Trick, S., Rothkopf, C.; Peters, J. (2019). Learning Intention Aware Online Adaptation of Movement Primitives, IEEE Robotics and Automation Letters (RA-L), with presentation at the IEEE International Conference on Intelligent Robots and Systems (IROS).   Download Article [PDF]   BibTeX Reference [BibTex]
4. Koert, D.; Trick, S.; Ewerton, M.; Lutter, M.; Peters, J. (2020). Incremental Learning of an Open-Ended Collaborative Skill Library, International Journal of Humanoid Robotics (IJHR), 17, 1.   BibTeX Reference [BibTex]
5. Koert, D.; Trick, S.; Ewerton, M.; Lutter, M.; Peters, J. (2018). Online Learning of an Open-Ended Skill Library for Collaborative Tasks, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   Download Article [PDF]   BibTeX Reference [BibTex]
6. Hoelscher, J.; Koert, D.; Peters, J.; Pajarinen, J. (2018). Utilizing Human Feedback in POMDP Execution and Specification, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   Download Article [PDF]   BibTeX Reference [BibTex]
7. Koert, D.; Maeda, G.; Neumann, G.; Peters, J. (2018). Learning Coupled Forward-Inverse Models with Combined Prediction Errors, Proceedings of the International Conference on Robotics and Automation (ICRA).   Download Article [PDF]   BibTeX Reference [BibTex]
8. Koert, D.; Maeda, G.J.; Lioutikov, R.; Neumann, G.; Peters, J. (2016). Demonstration Based Trajectory Optimization for Generalizable Robot Motions, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).   Download Article [PDF]   BibTeX Reference [BibTex]
9. S. Kohlbrecher, F. Kunz, D. Koert, C. Rose, P. Manns, K. Daun, J. Schubert, A. Stumpf, O. von Stryk (2014). Towards Highly Reliable Autonomy for Urban Search and Rescue Robots, Robot Soccer World Cup, pp.118-129, Springer International Publishing.   Download Article [PDF]   BibTeX Reference [BibTex]

Videos

Online Learning of an Open-Ended Skill Library for Collaborative Tasks?

Teaching

Teaching assistant for Projektkurs CE SoSe 2018

Teaching assistant for Statistical Machine Learning SoSe 2019

Supervision

• Master Thesis, "Reinforcement Learning and Implicit Feedback", Tosik, T. (ongoing)
• Master Thesis, "The Relation between Social Interaction and Intrinsic Motivation in Reinforcement Learning" Brendgen, J. (ongoing)
• Master Thesis , "Intuitive imitation learning for one-handed and bimanual tasks using ProMPs", Knaust, M. (2019)
• Master Thesis, "Learning from Human Feedback: A Comparison of Interactive Reinforcement Learning Algorithms", Kircher, M. (2019)
• Master Thesis, "Deep Robot Reinforcement Learning for Assisting a Human", Pal, S. (2019)
• Master Thesis, "Probabilistic Motion and Intention Prediction for Autonomous Vehicles", Jukonyte, L. (2019)
• Master Thesis, "Pedestrian Detection, Tracking and Intention Prediction in the Context of autonomous Driving", Hoffmann, D. (2019)
• Master Thesis, "Multimodal Uncertainty Reduction for Intention Recognition in a Human-Robot Environment" Trick, S. (2018)
• Master Thesis, “Comparison and Evaluation of Concepts for SLAM in the Context of Autonomous Driving”, Bug,D (2018)
• Master Thesis,"Interactive Planning Under Uncertainty', Hoelscher, J (2017)
• Bachelor Thesis, "Learning a library of Physical Interactions for Social Robots", Gassen, M. (ongoing)
• Bachelor Thesis, "Developing a Robot Head for Internal State Visualization", Vincenti, A. (2021)
• Bachelor Thesis, "Using Multimodal Human Feedback for Reinforcement Learning", Herbert, F. (2021)
• Bachelor Thesis, "Person Recognition via Videoand Audio Data", Andres, M., (2021)
• Bachelor Thesis, "Development of an Interactive Gesture Recognition System for an Assistive Robot", Schramm, M.(2020)
• Bachelor Thesis,"Comparison of Methods for Human Feedback as a Reward-Signal in Reinforcement Learning", Hellwig, J., (ongoing)
• Bachelor Thesis,"Integration of LIDAR SLAM for an automous vehicle", Kirschner, M., (2020)
• Bachelor Thesis, "Imitation Learning for Highlevel Robot behavior in the context of elderly assistance", Lang, M. (2019)
• Bachelor Thesis, "Trajectory Based Upper Body Gesture Recognition for an Assistive Robot", Divo, F. (2019)
• Bachelor Thesis, "Towards a Robot Skill Library Using Hierarchy, Composition and Adaptation", Kaiser, F. (2019)
• Bachelor Thesis, "Collision Avoidance in Uncertain Environments for Autonomous Vehicles using POMDPs", Schotschneider, A (2018)
• Bachelor Thesis. Development and Evaluation of 3D Autoencoders for Feature Extraction, Hesse, R. (2017)
• Bachelor Thesis, "Matching Bundles of Axons Using Feature Graphs" Zecevic, M. (2017).
• Bachelor Thesis, "Transferring Insights on Mental Training to Robot Motor Skill Learning", Szelag, S. (2017)
• Bachelor Thesis, "Transferring Insights on Biological Sleep to Robot Motor Skill Learning", Rother, D (2017)