4 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…
Achieving Human Level Competitive Robot Table Tennis
David B. D'Ambrosio, Saminda Abeyruwan, Laura Graesser +24
Achieving human-level speed and performance on real world tasks is a north star for the robotics research community. This work takes a step towards that goal and presents the first…
Robotic Table Tennis: A Case Study into a High Speed Learning System
David B. D'Ambrosio, Jonathan Abelian, Saminda Abeyruwan +32
We present a deep-dive into a real-world robotic learning system that, in previous work, was shown to be capable of hundreds of table tennis rallies with a human and has the abilit…
Learning to Learn Faster from Human Feedback with Language Model Predictive Control
Jacky Liang, Fei Xia, Wenhao Yu +47
Large language models (LLMs) have been shown to exhibit a wide range of capabilities, such as writing robot code from language commands -- enabling non-experts to direct robot beha…