103 citations · 131 across the 7 of their papers we have counts for
7 papers
Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer
Gemini Robotics Team, Abbas Abdolmaleki, Saminda Abeyruwan +169
General-purpose robots need a deep understanding of the physical world, advanced reasoning, and general and dexterous control. This report introduces the latest generation of the G…
Gemini Robotics: Bringing AI into the Physical World
Gemini Robotics Team, Saminda Abeyruwan, Joshua Ainslie +115
Recent advancements in large multimodal models have led to the emergence of remarkable generalist capabilities in digital domains, yet their translation to physical agents such as…
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…
AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents
Michael Ahn, Debidatta Dwibedi, Chelsea Finn +24
Foundation models that incorporate language, vision, and more recently actions have revolutionized the ability to harness internet scale data to reason about useful tasks. However,…
SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention
Isabel Leal, Krzysztof Choromanski, Deepali Jain +11
We present Self-Adaptive Robust Attention for Robotics Transformers (SARA-RT): a new paradigm for addressing the emerging challenge of scaling up Robotics Transformers (RT) for on-…
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches
Jiayuan Gu, Sean Kirmani, Paul Wohlhart +14
Generalization remains one of the most important desiderata for robust robot learning systems. While recently proposed approaches show promise in generalization to novel objects, s…
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…