356 citations · 853 across the 24 of their papers we have counts for
4 papers · 2 filters
Foundation Models in Robotics: Applications, Challenges, and the Future
Roya Firoozi, Johnathan Tucker, Stephen Tian +12
We survey applications of pretrained foundation models in robotics. Traditional deep learning models in robotics are trained on small datasets tailored for specific tasks, which li…
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…
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
Anthony Brohan, Noah Brown, Justice Carbajal +51
We study how vision-language models trained on Internet-scale data can be incorporated directly into end-to-end robotic control to boost generalization and enable emergent semantic…
Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents
Wenlong Huang, Fei Xia, Dhruv Shah +8
Recent progress in large language models (LLMs) has demonstrated the ability to learn and leverage Internet-scale knowledge through pre-training with autoregressive models. Unfortu…