[1/N] Large flow policies (e.g., VLAs) have become extremely popular, unlocking scalability. However, they come at a cost: the robot cannot react quickly. π𝐑² enables them to achieve reactive, real-time control.

Join us at ICRA 2026 if you are interested in dexterous hands 👋

Check out Dex4D from

: a framework for zero-shot dexterous manipulation in the real world via a two-level system.🎥 Video generation + 🎯 point tracks act as a high-level planner, while a 🤖 task-agnostic policy trained in simulation serves as the low-level controller.

If you are working on robot learning, apply to JHU and work with Homanga (

)! You’ll be able to freely discuss about diverse and important topics, with hands-on guidance for all aspects of research! (I was lucky to have him as my mentor 🙂)