3 papers
cs.RO2026
VLAgents: A Policy Server for Efficient VLA Inference
Tobias Jülg, Khaled Gamal, Nisarga Nilavadi +5
The rapid emergence of Vision-Language-Action models (VLAs) has a significant impact on robotics. However, their deployment remains complex due to the fragmented interfaces and the…
cs.RO2025
Augmented Reality for RObots (ARRO): Pointing Visuomotor Policies Towards Visual Robustness
Reihaneh Mirjalili, Tobias Jülg, Florian Walter +1
Visuomotor policies trained on human expert demonstrations have recently shown strong performance across a wide range of robotic manipulation tasks. However, these policies remain…
cs.RO2025
Refined Policy Distillation: From VLA Generalists to RL Experts
Tobias Jülg, Wolfram Burgard, Florian Walter
Vision-Language-Action Models (VLAs) have demonstrated remarkable generalization capabilities in real-world experiments. However, their success rates are often not on par with expe…