Shaohang Han — accepted AI-conference papers

2025

CageCoOpt: Enhancing Manipulation Robustness through Caging-Guided Morphology and Policy Co-Optimization

Yifei Dong, Shaohang Han, Xianyi Cheng, Werner Friedl, Rafael I. Cabral Muchacho, Máximo A. Roa +2

IROS 2025

Uncertainties in contact dynamics and object geometry remain significant barriers to robust robotic manipulation. Caging helps mitigate these uncertainties by constraining an object’s mobility without requiring precise contact modeling. Existing caging research often treats morphology and policy opt

Cited by 9 Source ↗Scholar ↗

2023

Reinforcement Learning for Safe Robot Control using Control Lyapunov Barrier Functions

Desong Du, Shaohang Han, Naiming Qi, Haitham Bou Ammar, Jun Wang, Wei Pan

ICRA 2023poster

Reinforcement learning (RL) exhibits impressive performance when managing complicated control tasks for robots. However, its wide application to physical robots is limited by the absence of strong safety guarantees. To overcome this challenge, this paper explores the control Lyapunov barrier functio…

Cited by 18 Source ↗Scholar ↗