In my research, I investigate learning-based methods for the representation and generation of CAD geometry. A particular focus lies on the assembly context, since mechanical parts are not designed in isolation but as components of larger assemblies. I explore how this context can be incorporated into generative models to generate parts that fit their surrounding assembly.
Fabian Baumeister, M.Sc.
- Research Associate
- Learning-based representation and generation of CAD geometry
- room: 261
CS 20.20 - phone: +49 721 608-47957
- fabian baumeister ∂does-not-exist.kit edu
- Zirkel 2
76131 Karlsruhe
Publikationen
Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation Using Parallelizable Physics Simulators
Baumeister, F.; Mack, L.; Stueckler, J.
2025. 2025 IEEE International Conference on Robotics and Automation (ICRA), Atlanta, GA, USA, 19-23 May 2025, 15394–15400, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICRA55743.2025.11128222
Baumeister, F.; Mack, L.; Stueckler, J.
2025. 2025 IEEE International Conference on Robotics and Automation (ICRA), Atlanta, GA, USA, 19-23 May 2025, 15394–15400, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICRA55743.2025.11128222
Learning-based 3D CAD model generation in mechanical engineering: A survey
Baumeister, F.; Bönsch, J.; Chaumet, C.; Dörr, L.; Meyer, A.
2026. Advanced Engineering Informatics, 76, 104990. doi:10.1016/j.aei.2026.104990
Baumeister, F.; Bönsch, J.; Chaumet, C.; Dörr, L.; Meyer, A.
2026. Advanced Engineering Informatics, 76, 104990. doi:10.1016/j.aei.2026.104990