90 citations · 102 across the 10 of their papers we have counts for
10 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…
A Survey on Imitation Learning for Contact-Rich Tasks in Robotics
Toshiaki Tsuji, Yasuhiro Kato, Gokhan Solak +4
This paper comprehensively surveys research trends in imitation learning for contact-rich robotic tasks. Contact-rich tasks, which require complex physical interactions with the en…
ExoStart: Efficient learning for dexterous manipulation with sensorized exoskeleton demonstrations
Zilin Si, Jose Enrique Chen, M. Emre Karagozler +15
Recent advancements in teleoperation systems have enabled high-quality data collection for robotic manipulators, showing impressive results in learning manipulation at scale. This…
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…
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,…
DemoStart: Demonstration-led auto-curriculum applied to sim-to-real with multi-fingered robots
Maria Bauza, Jose Enrique Chen, Valentin Dalibard +13
We present DemoStart, a novel auto-curriculum reinforcement learning method capable of learning complex manipulation behaviors on an arm equipped with a three-fingered robotic hand…
Using PT-symmetric Qubits to Break the Tradeoff Between Fidelity and the Degree of Quantum Entanglement
B. -B. Liu, Shi-Lei Su, Y. -L. Zuo +4
A noteworthy discovery is that the minimal evolution time is smaller for parity-time () symmetric systems compared to Hermitian setups. Moreover, there is a significa…
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning
Dhruva Tirumala, Markus Wulfmeier, Ben Moran +13
We apply multi-agent deep reinforcement learning (RL) to train end-to-end robot soccer policies with fully onboard computation and sensing via egocentric RGB vision. This setting r…
Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots
Thomas Lampe, Abbas Abdolmaleki, Sarah Bechtle +12
Reinforcement learning solely from an agent's self-generated data is often believed to be infeasible for learning on real robots, due to the amount of data needed. However, if done…
Speed limits for quantum gates in multi-qubit systems
S. Ashhab, P. C. de Groot, Franco Nori
We use analytical and numerical calculations to obtain speed limits for various unitary quantum operations in multiqubit systems under typical experimental conditions. The operatio…