Georgia Chalvatzaki Team
Georgia Chalvatzaki
Quick Info
Research Interests
Robotics; Perception Systems; Mobile manipulation; Deep Learning; Deep Reinforcement Learning; Human-Robot Interaction & Collaboration
More Information
https://irosalab.com/ Linkedin Google Scholar Curriculum Vitae
Contact Information
Mail. Georgia Chalvatzaki, FG-iROSA, FB-Informatik, TU Darmstadt, Hochschulstr 10, 64289 Darmstadt
Office. Room D203, S2|02
(lab) +49-6151-16-21814
georgia.chalvatzaki@tu-darmstadt.de
New site for the iROSA group: https://irosalab.com/
Georgia Chalvatzaki is an Full Professor at TU Darmstadt since April 2023. Before that, she was an Independednt Research Group Leader from March 2021, after getting the renowned Emmy Noether Programme (ENP) fund of the German Research Foundation (DFG). This project was awarded within the ENP Artificial Intelligence call of the DFG – only 9 proposals out of 91 proposals were selected for funding. It enables outstanding young scientists to qualify for a university professorship by independently leading a junior research group over six years.
In her research group iROSA, Dr. Chalvatzaki and her new team will research the topic of "Robot Learning of Mobile Manipulation for Assistive Robotics". Dr. Chalvatzaki proposes new methods at the intersection of machine learning and classical robotics, taking one step further the research for embodied AI robotic assistants. The research in iROSA proposes novel methods for combined planning and learning for enabling mobile manipulator robots to solve complex tasks in house-like environments, with the human-in-the-loop of the interaction process.
From October 2019, she was a Postodoctoral researcher at the Intelligent Autonous Systems group, advised by Jan Peters. Dr. Chalvatzaki completed her Ph.D. studies in 2019 at the Intelligent Robotics and Automation Lab (https://robotics.ntua.gr/ ) at the Electrical and Computer Engineering School of the National Technical University of Athens, Greece, with her thesis "Human-Centered Modeling for Assistive Robotics: Stochastic Estimation and Robot Learning in Decision Making." During her career, she has worked on eight research projects, and she has published more than 30 papers ((https://scholar.google.com/citations?user=mlho5FkAAAAJ&hl=en ) ), most of which in top-tier robotics and machine learning venues, e.g., ICRA, IROS, RA-L.
Key references
Liu, Y.; Belousov, B.; Funk, N.; Chalvatzaki, G.; Peters, J.; Tessman, O. (2023). Auto(mated)nomous Assembly, International Conference on Trends on Construction in the Post-Digital Era, pp.167-181, Springer, Cham.
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Liu, P.; Zhang, K.; Tateo, D.; Jauhri, S.; Hu, Z.; Peters, J. Chalvatzaki, G. (2023). Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction, 2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE.
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Hansel, K.; Urain, J.; Peters, J.; Chalvatzaki, G. (2023). Hierarchical Policy Blending as Inference for Reactive Robot Control, 2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE.
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Dam, T.; Chalvatzaki, G.; Peters, J.; Pajarinen J. (2022). Monte-Carlo Robot Path Planning, IEEE Robotics and Automation Letters, and 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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Belousov, B.; Wibranek, B.; Schneider, J.; Schneider, T.; Chalvatzaki, G.; Peters, J.; Tessmann, O. (2022). Robotic Architectural Assembly with Tactile Skills: Simulation and Optimization, Automation in Construction, 133, pp.104006.
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D`Eramo, C.; Chalvatzaki, G. (2022). Prioritized Sampling with Intrinsic Motivation in Multi-Task Reinforcement Learning, International Joint Conference on Neural Networks (IJCNN).
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Urain, J.; Le, A.T.; Lambert, A.; Chalvatzaki, G.; Boots, B.; Peters, J. (2022). Learning Implicit Priors for Motion Optimization, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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Funk, N.; Menzenbach, S.; Chalvatzaki, G.; Peters, J. (2022). Graph-based Reinforcement Learning meets Mixed Integer Programs: An application to 3D robot assembly discovery, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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Schneider, T.; Belousov, B.; Chalvatzaki, G.; Romeres, D.; Jha, D.K.; Peters, J. (2022). Active Exploration for Robotic Manipulation, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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Prasad, V.; Koert, D.; Stock-Homburg, R.; Peters, J.; Chalvatzaki, G. (2022). MILD: Multimodal Interactive Latent Dynamics for Learning Human-Robot Interaction, IEEE-RAS International Conference on Humanoid Robots (Humanoids).
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Le, A. T.; Hansel, K.; Peters, J.; Chalvatzaki, G. (2022). Hierarchical Policy Blending As Optimal Transport, 5th Annual Learning for Dynamics & Control Conference (L4DC), PMLR.
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Tosatto, S.; Chalvatzaki, G.; Peters, J. (2021). Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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Li, Q.; Chalvatzaki, G.; Peters, J.; Wang, Y. (2021). Directed Acyclic Graph Neural Network for Human Motion Prediction, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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Morgan, A.; Nandha, D.; Chalvatzaki, G.; D'Eramo, C.; Dollar, A.; Peters, J. (2021). Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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Funk, N.; Chalvatzaki, G.; Belousov, B.; Peters, J. (2021). Learn2Assemble with Structured Representations and Search for Robotic Architectural Construction, Conference on Robot Learning (CoRL).
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Chalvatzaki, G.;Papageorgiou, X.; Maragos, P.; Tzafestas, C. (2019). Learn to adapt to human walking: A Model-based Reinforcement Learning Approach for a Robotic Assistant Rollator, in: IEEE (eds.), IEEE Robotics and Automation Letters, 4, 4, pp.3774 - 3781.
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Chalvatzaki, G.; Koutras, P.; Hadfield, J.; Papageorgiou, X.; Tzafestas, C.; Maragos, P. (2019). LSTM-based Network for Human Gait Stability Prediction in an Intelligent Robotic Rollator, IEEE International Conference on Robotics and Automation (ICRA), pp.4225-4232, IEEE.
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Chalvatzaki, G.; Papageorgiou, X.; Tzafestas, C.; Maragos, P. (2018). Augmented Human State Estimation Using Interacting Multiple Model Particle Filters With Probabilistic Data Association, IEEE Robotics and Automation Letters, 3, 3, pp.1872-1879, IEEE.
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Chalvatzaki, G.;Papageorgiou, X.; Maragos, P.; Tzafestas, C. (2018). User-Adaptive Human-Robot Formation Control for an Intelligent Robotic Walker Using Augmented Human State Estimation and Pathological Gait Characterization, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.6016-6022, IEEE.
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Chalvatzaki, G.; Papageorgiou, X.; Tzafestas, C.; Maragos, P. (2017). Comparative experimental validation of human gait tracking algorithms for an intelligent robotic rollator, IEEE International Conference on Robotics and Automation (ICRA), pp.6026-6031, IEEE.
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Chalvatzaki, G.; Papageorgiou, X.; Tzafestas, C. (2017). Towards a user-adaptive context-aware robotic walker with a pathological gait assessment system: First experimental study, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.5037-5042, IEEE.
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