Tobias Thomas Jülg — accepted AI-conference papers

2026

Augmented Reality for RObots (ARRO): Pointing Visuomotor Policies towards Visual Robustness

Reihaneh Mirjalili, Tobias Thomas Jülg, Florian Walter, Wolfram Burgard

ICRA 2026poster

Visuomotor policies trained on human expert demonstrations have recently shown strong performance across a wide range of robotic manipulation tasks. However, these policies remain highly sensitive to domain shifts stemming from background or robot embodiment changes, which limits their generalizatio…

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2026

Robot Control Stack: A Lean Ecosystem for Robot Learning at Scale

Tobias Thomas Jülg, Pierre Krack, Seongjin Bien, Yannik Blei, Khaled Gamal, Ken Nakahara +4

ICRA 2026poster

Vision-Language-Action models (VLAs) mark a major shift in robot learning. They replace specialized architectures and task-tailored components of expert policies with large-scale data collection and setup-specific fine-tuning. In this machine learning-focused workflow that is centered around models …

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