254 citations · 255 across the 4 of their papers we have counts for
5 papers
Box-WAM: Box Trajectories as Compact State Representations for World Action Models
Qinxi Yu, Wenzhou Ding, Gloria X. Wang +2
World action models (WAMs) are a category of policy models that ex- plicitly predict both actions and future world states. They have been shown to outperform action-only models acr…
Lucid-XR: An Extended-Reality Data Engine for Robotic Manipulation
Yajvan Ravan, Adam Rashid, Alan Yu +8
We introduce Lucid-XR, a generative data engine for creating diverse and realistic-looking multi-modal data to train real-world robotic systems. At the core of Lucid-XR is vuer, a…
EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos
Ruihan Yang, Qinxi Yu, Yecheng Wu +12
Real robot data collection for imitation learning has led to significant advancements in robotic manipulation. However, the requirement for robot hardware in the process fundamenta…
ORBIT-Surgical: An Open-Simulation Framework for Learning Surgical Augmented Dexterity
Qinxi Yu, Masoud Moghani, Karthik Dharmarajan +8
Physics-based simulations have accelerated progress in robot learning for driving, manipulation, and locomotion. Yet, a fast, accurate, and robust surgical simulation environment r…
Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments
Mayank Mittal, Calvin Yu, Qinxi Yu +12
We present Orbit, a unified and modular framework for robot learning powered by NVIDIA Isaac Sim. It offers a modular design to easily and efficiently create robotic environments w…