SCIoI Alumni

Manuel Baum

Doctoral Researcher

Robotics

TU Berlin

 

Email:
baum@tu-berlin.de

 

Photo: SCIoI

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Manuel Baum

Manuel Baum

Photo: SCIoI

After obtaining his Bachelor’s degree in Cognitive Informatics and his Master’s degree in Intelligent Systems, both at Bielefeld University, Manuel Baum started to work on his  Doctoral degree at the Robotics and Biology Laboratory at TU Berlin and then also became a member of SCIoI. Robots and animals need to solve tasks, but for some tasks the information required is unknown until the agent actually starts to solve a problem, and it needs to be gathered interactively. But which information is actually task-relevant, and how can a robot / animal gather that information? This was the subject of task-directed exploration and interactive perception, which are Manuel’s two main research interests. In the SCIoI project “Intelligent kinematic problem solving”, together with colleagues from Berlin, Oxford and Vienna, Manuel researched how cockatoos and robots can explore, understand and solve complex mechanical puzzles.


Projects

Manuel Baum is member of Project 04.


Baum, M., Schattenhofer, L., Rössler, T., Osuna-Mascaro, A., Auersperg, A., Kacelnik, A., & Brock, O. (2024). Mechanical Problem Solving in Goffin’s Cockatoos - Towards Modeling Complex Behavior. Adaptive Behavior. https://doi.org/10.1177/10597123241270764
Baum, J., Eiserbeck, A., Maier, M., & Abdel Rahman, R. (2024). The evaluation of presumed deepfakes with different basic emotional expressions depends on valence. Psychologie und Gehirn.
Eiserbeck, A., Maier, M., Baum, J., & Abdel Rahman, R. (2023). Deepfake smiles matter less—the psychological and neural impact of presumed AI-generated faces. Scientific Reports. https://doi.org/10.1038/s41598-023-42802-x
Mengers, V., Battaje, A., Baum, M., & Brock, O. (2023). Combining Motion and Appearance for Robust Probabilistic Object Segmentation in Real Time. ICRA 2023. https://doi.org/10.1109/ICRA48891.2023.10160908
Li, X., Baum, M., & Brock, O. (2023). Augmentation Enables One-Shot Generalization In Learning From Demonstration for Contact-Rich Manipulation. IROS 2023. https://doi.org/10.1109/IROS55552.2023.10341625
Baum, M., Froessl, A., Battaje, A., & Brock, O. (2023). Estimating the Motion of Drawers From Sound. ICRA 2023. https://doi.org/10.1109/ICRA48891.2023.10161399
Baum, M., Schattenhofer, L., Rössler, T., Osuna-Mascaro, A., Auersperg, A., Kacelnik, A., & Brock, O. (2022). Yoking-Based Identification of Learning Behavior in Artificial and Biological Agents. SAB 2022. https://doi.org/10.1007/978-3-031-16770-6_6
Baum, M., & Brock, O. (2022). “The World Is Its Own Best Model”: Robust Real-World Manipulation Through Online Behavior Selection. ICRA 2022. https://doi.org/10.1109/ICRA46639.2022.9811845
Baum, M., & Brock, O. (2021). Achieving Robustness in a Drawer Manipulation Task by using High-level Feedback instead of Planning. DGR Days. https://www.static.tu.berlin/fileadmin/www/10002220/Publications/baum21DGR.pdf

Wissen aus Berlin - 4 October 2022 - Intelligent Kinematic Problem Solving

Research

An overview of our scientific work

See our Research Projects