21 citations · 22 across the 21 of their papers we have counts for
7 papers · 1 filter
ConPoSe: LLM-Guided Contact Point Selection for Scalable Cooperative Object Pushing
Noah Steinkrüger, Nisarga Nilavadi, Wolfram Burgard +1
Object transportation in cluttered environments is a fundamental task in various domains, including domestic service and warehouse logistics. In cooperative object transport, multi…
Robot Control Stack: A Lean Ecosystem for Robot Learning at Scale
Tobias Jülg, Pierre Krack, Seongjin Bien +7
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 d…
MetricNet: Recovering Metric Scale in Generative Navigation Policies
Abhijeet Nayak, Débora Oliveira Makowski, Samiran Gode +2
Generative navigation policies have made rapid progress in improving end-to-end learned navigation. Despite their promising results, this paradigm has two structural problems. Firs…
A roadmap for AI in robotics
Aude Billard, Alin Albu-Schaeffer, Michael Beetz +8
AI technologies, including deep learning, large-language models have gone from one breakthrough to the other. As a result, we are witnessing growing excitement in robotics at the p…
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…
iPack: Intuitive Bin Packing with Large Language Models
Yannik Blei, Michael Krawez, Adrian Göß +5
Robotics and automation are increasingly influential in logistics but remain largely confined to traditional warehouses. In grocery retail, advancements such as cashier-less superm…
REGRACE: A Robust and Efficient Graph-based Re-localization Algorithm using Consistency Evaluation
Débora N. P. Oliveira, Joshua Knights, Sebastián Barbas Laina +3
Loop closures are essential for correcting odometry drift and creating consistent maps, especially in the context of large-scale navigation. Current methods using dense point cloud…