Xiaomeng Xu

Task-dependent action frames can enhance robotic manipulation performance, with MoF outperforming traditional single-frame policies in both simulation and real-world applications.

This vine robot can autonomously navigate and manipulate in complex environments, overcoming traditional control limitations with a robust vision-based approach.

Scaling robot learning with human data isn't a simple "more is better" equation; alignment with robot learning objectives is key.