6 citations · 6 across the 4 of their papers we have counts for
4 papers
DUET-DINO: Simultaneous Cross-View World Modeling for Latent Planning in Robot Manipulation
Nisarga Nilavadi, Ralf Römer, Moritz Reuss +5
Action-conditioned latent world models predict future visual representations, enabling zero-shot goal-conditioned robot planning and control. However, their predictions for fine-gr…
Learning Where it Matters: Autonomous Data Collection and Offline Reinforcement Learning for Local Contact-Rich Manipulation
Oliver Hausdörfer, Linus Schwarz, Gabor Marko +7
Learned policies trained end-to-end on large datasets often remain brittle in high-precision contact-rich tasks. Further, they typically require large amounts of manually collected…
CLARE: Continual Learning for Vision-Language-Action Models via Autonomous Adapter Routing and Expansion
Ralf Römer, Yi Zhang, Yuming Li +1
To teach robots complex manipulation tasks, a common approach is to fine-tune a pre-trained vision-language-action model (VLA) on task-specific data. However, since this recipe upd…
Vision-Based Uncertainty-Aware Motion Planning based on Probabilistic Semantic Segmentation
Ralf Römer, Armin Lederer, Samuel Tesfazgi +1
For safe operation, a robot must be able to avoid collisions in uncertain environments. Existing approaches for motion planning under uncertainties often assume parametric obstacle…