14 citations · 32 across the 21 of their papers we have counts for
4 papers · 1 filter
cVLA: Towards Efficient Camera-Space VLAs
Max Argus, Jelena Bratulic, Houman Masnavi +4
Vision-Language-Action (VLA) models offer a compelling framework for tackling complex robotic manipulation tasks, but they are often expensive to train. In this paper, we propose a…
Learning Robotic Manipulation Policies from Point Clouds with Conditional Flow Matching
Eugenio Chisari, Nick Heppert, Max Argus +3
Learning from expert demonstrations is a promising approach for training robotic manipulation policies from limited data. However, imitation learning algorithms require a number of…
DITTO: Demonstration Imitation by Trajectory Transformation
Nick Heppert, Max Argus, Tim Welschehold +2
Teaching robots new skills quickly and conveniently is crucial for the broader adoption of robotic systems. In this work, we address the problem of one-shot imitation from a single…
Compositional Servoing by Recombining Demonstrations
Max Argus, Abhijeet Nayak, Martin Büchner +3
Learning-based manipulation policies from image inputs often show weak task transfer capabilities. In contrast, visual servoing methods allow efficient task transfer in high-precis…