11 citations · 33 across the 10 of their papers we have counts for
11 papers
: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities
Physical Intelligence, Bo Ai, Ali Amin +85
We present a new robotic foundation model, called , that can enable strong out-of-the-box performance in a wide range of scenarios. can follow diverse language i…
Training-Time Action Conditioning for Efficient Real-Time Chunking
Kevin Black, Allen Z. Ren, Michael Equi +1
Real-time chunking (RTC) enables vision-language-action models (VLAs) to generate smooth, reactive robot trajectories by asynchronously predicting action chunks and conditioning on…
: a VLA That Learns From Experience
Physical Intelligence, Ali Amin, Raichelle Aniceto +53
We study how vision-language-action (VLA) models can improve through real-world deployments via reinforcement learning (RL). We present a general-purpose method, RL with Experience…
Real-Time Execution of Action Chunking Flow Policies
Kevin Black, Manuel Y. Galliker, Sergey Levine
Modern AI systems, especially those interacting with the physical world, increasingly require real-time performance. However, the high latency of state-of-the-art generalist models…
Towards Embodiment Scaling Laws in Robot Locomotion
Bo Ai, Liu Dai, Nico Bohlinger +7
Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…
: a Vision-Language-Action Model with Open-World Generalization
Physical Intelligence, Kevin Black, Noah Brown +33
In order for robots to be useful, they must perform practically relevant tasks in the real world, outside of the lab. While vision-language-action (VLA) models have demonstrated im…
: A Vision-Language-Action Flow Model for General Robot Control
Kevin Black, Noah Brown, Danny Driess +21
Robot learning holds tremendous promise to unlock the full potential of flexible, general, and dexterous robot systems, as well as to address some of the deepest questions in artif…
Octo: An Open-Source Generalist Robot Policy
Octo Model Team, Dibya Ghosh, Homer Walke +16
Large policies pretrained on diverse robot datasets have the potential to transform robotic learning: instead of training new policies from scratch, such generalist robot policies…
Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control
Masatoshi Uehara, Yulai Zhao, Kevin Black +6
Diffusion models excel at capturing complex data distributions, such as those of natural images and proteins. While diffusion models are trained to represent the distribution in th…
Feedback Efficient Online Fine-Tuning of Diffusion Models
Masatoshi Uehara, Yulai Zhao, Kevin Black +6
Diffusion models excel at modeling complex data distributions, including those of images, proteins, and small molecules. However, in many cases, our goal is to model parts of the d…
Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models
Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya +4
If generalist robots are to operate in truly unstructured environments, they need to be able to recognize and reason about novel objects and scenarios. Such objects and scenarios m…