most citedGemini Robotics: Bringing AI into the Physical World

6 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2025★ 1 cited

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…

cs.RO2025★ 6 cited

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…

cs.RO2025

Proc4Gem: Foundation models for physical agency through procedural generation

Yixin Lin, Jan Humplik, Sandy H. Huang +18

In robot learning, it is common to either ignore the environment semantics, focusing on tasks like whole-body control which only require reasoning about robot-environment contacts,…

cs.RO2024

Prosody for Intuitive Robotic Interface Design: It's Not What You Said, It's How You Said It

Elaheh Sanoubari, Atil Iscen, Leila Takayama +3

In this paper, we investigate the use of 'prosody' (the musical elements of speech) as a communicative signal for intuitive human-robot interaction interfaces. Our approach, rooted…

cs.RO2024★ 1 cited

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…