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 is now also 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 is 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 researches how cockatoos and robots can explore, understand and solve complex mechanical puzzles.
At SCIoI, Manuel is working on Project 04, “Intelligent kinematic problem solving.”
2756394 Baum items 1 author desc year
Mengers, V., Battaje, A., Baum, M., & Brock, O. (2023). Combining Motion and Appearance for Robust Probabilistic Object Segmentation in Real Time. ICRA 2023.
Baum, M., Froessl, A., Battaje, A., & Brock, O. (2023). Estimating the Motion of Drawers From Sound. ICRA 2023.
Baum, M., Schattenhofer, L., Rössler, T., Osuna-Mascaró, 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. http://www.robotics.tu-berlin.de/fileadmin/fg170/Publikationen_pdf/baum21DGR.pdf