Si-Heng Zhao

This work presents HOTICE, a whole-body humanoid learning framework for transporting objects through cluttered environments, and introduces Humanoid-Object Decoupled Potential Fields, which jointly encode collision-avoidance guidance for the robot and the carried object, enabling coordinated, obstacle-aware motion for both.

LadderMan enables humanoid robots to climb ladders and manipulate objects with unprecedented robustness and adaptability in real-world scenarios.

Forget tedious manual calibration: D-REX automatically builds high-fidelity digital twins by identifying object mass directly from real-world grasping data.