Han Xue

FA-RDP achieves superior success rates in contact-rich manipulation while preserving diverse action modes, revolutionizing how we approach multimodal decision-making in robotics.

LIFT accelerates learning in vision-language-action policies by injecting reactive force feedback, achieving superior performance in contact-rich tasks.

Robots can now learn complex manipulation tasks directly from human demonstrations using only a pair of smart glasses, achieving zero-shot transfer without specialized hardware.

Fisheye cameras in robotics offer superior scene generalization, but only if you train them with enough environmental diversity to avoid overfitting.