Chuyue Guan — accepted AI-conference papers

2026

MLM: Learning Multi-Task Loco-Manipulation Whole-Body Control for Quadruped Robot With Arm

Xin Liu, Bida Ma, Chenkun Qi, Yan Ding, Nuo Xu, Zhaxizhuoma +11

RA-L 2026

Whole-body loco-manipulation for quadruped robots with arms remains a challenging problem, particularly in achieving multi-task control. To address this, we propose MLM, a reinforcement learning framework driven by both real-world and simulation data. It enables a six-DoF robotic arm–equipped quadru

Cited by 4 Source ↗Scholar ↗

2025

FastUMI: A Scalable and Hardware-Independent Universal Manipulation Interface with Dataset

Zhaxizhuoma, Kehui Liu, Chuyue Guan, Zhongjie Jia, Ziniu Wu, Xin Liu +12

CoRL 2025poster

Real-world manipulation datasets for robotic arms remain scarce due to the high costs, rigid hardware dependencies, and complex setup procedures associated with existing data collection methods. We introduce, a redesigned Universal Manipulation Interface (UMI) that addresses these challenges, enabli…

Cited by 0 Source ↗Scholar ↗