103 citations · 138 across the 13 of their papers we have counts for
3 papers · 1 filter
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Embodiment Collaboration, Abby O'Neill, Abdul Rehman +291
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, thi…
Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80
Vincent Berenz, Felix Widmaier, Simon Guist +2
Robotic applications require the integration of various modalities, encompassing perception, control of real robots and possibly the control of simulated environments. While the st…
Hindsight States: Blending Sim and Real Task Elements for Efficient Reinforcement Learning
Simon Guist, Jan Schneider, Alexander Dittrich +3
Reinforcement learning has shown great potential in solving complex tasks when large amounts of data can be generated with little effort. In robotics, one approach to generate trai…