Dorothea Koert

Research Interests
Human-Robot Interaction, Robot Skill Learning, Interactive Machine Learning, Learning from Demonstration, Interactive Reinforcement Learning
Affiliation
- IKIDA Research Group, Center for Cognitive Science, TU Darmstadt and
- Intelligent Autonomous Systems, Computer Science Department, TU Darmstadt
Contact
Dorothea Koert is an Independent Research Group Leader of the interdisciplinary BMBF junior research group IKIDA which started in October 2020.
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.
Before the IKIDA project she was working on the KOBO project to improve the social participation of elderly people and maintaining their independence with a humanoid service robot. 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.
Dorothea cares deeply about teaching and supervision and has supervised more than 25 Master's and Bachelor's thesis as well as various directed research projects, see here for details. Please see her Curriculum Vitae for more details.
Key References
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- Scherf, L.; Schmidt, A.; Pal, S.; Koert, D. (2023). Interactively learning behavior trees from imperfect human demonstrations, Frontiers in Robotics and AI, 10.
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- Salikutluk, V.; Koert, D.; Jäkel, F. (2023). Interacting with Large Language Models: A Case Study on AI-Aided Brainstorming for Guesstimation Problems, The second International Conference on Hybrid Human-Artificial Intelligence.
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- Trick, S.; Lott, V.; Scherf, L.; Rothkopf, C. A.; Koert, D. (2023). What Can I Help You With: Towards Task-Independent Detection of Intentions for Interaction in a Human-Robot Environment, 32th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN).
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- Gassen, M.; Metzler, F.; Prescher, E.; Prasad, V.; Scherf, L. Kaiser, F.; Koert, D. (2023). I^3: Interactive Iterative Improvement for Few-Shot Action Segmentation, 32th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN).
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- Trick, S.; Herbert, F.; Rothkopf, C.A.; Koert, D. (2022). Interactive reinforcement learning with Bayesian fusion of multimodal advice, IEEE Robotics and Automation Letters 7 (RA-L), pp.7558-7565.
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- Scherf, L.; Turan, C.; Koert, D. (2022). Learning from Unreliable Human Action Advice in Interactive Reinforcement Learning, 2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids).
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- 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).
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- 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.
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- 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).
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- 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.
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- 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).
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- 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).
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- 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).
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- 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).
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- 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.
Her complete publications list can be found Here