4 papers
Extreme-RGMT: Continual Learning of Highly Dynamic Skills for Robust Generalist Humanoid Control
Yubiao Ma, Han Yu, Kai Guo +5
Humans can progressively acquire highly dynamic motor skills while preserving reliable everyday motor abilities. In contrast, existing humanoid controllers face a trade-off between…
Multi-Gait Learning for Humanoid Robots Using Reinforcement Learning with Selective Adversarial Motion Prior
Yuanye Wu, Keyi Wang, Linqi Ye +1
Learning diverse locomotion skills for humanoid robots in a unified reinforcement learning framework remains challenging due to the conflicting requirements of stability and dynami…
Robust and Generalized Humanoid Motion Tracking
Yubiao Ma, Han Yu, Jiayin Xie +7
Learning a general humanoid whole-body controller is challenging because practical reference motions can exhibit noise and inconsistencies after being transferred to the robot doma…
STEP Planner: Constructing cross-hierarchical subgoal tree as an embodied long-horizon task planner
Tianxing Zhou, Zhirui Wang, Haojia Ao +5
The ability to perform reliable long-horizon task planning is crucial for deploying robots in real-world environments. However, directly employing Large Language Models (LLMs) as a…