5 papers
A Definition and Roadmap for World Models
Xinyuan Chen, Haoyu Guo, Shi Guo +10
World models -- internal simulators that learn the structure and dynamics of an environment -- have become one of the most actively debated concepts in AI. From model-based reinfor…
Scalable and General Whole-Body Control for Cross-Humanoid Locomotion
Yufei Xue, YunFeng Lin, Wentao Dong +6
Learning-based whole-body controllers have become a key driver for humanoid robots, yet most existing approaches require robot-specific training. In this paper, we study the proble…
Embodiment-Aware Generalist Specialist Distillation for Unified Humanoid Whole-Body Control
Quanquan Peng, Yunfeng Lin, Yufei Xue +2
Humanoid Whole-Body Controllers trained with reinforcement learning (RL) have recently achieved remarkable performance, yet many target a single robot embodiment. Variations in dyn…
H-Zero: Cross-Humanoid Locomotion Pretraining Enables Few-shot Novel Embodiment Transfer
Yunfeng Lin, Minghuan Liu, Yufei Xue +4
The rapid advancement of humanoid robotics has intensified the need for robust and adaptable controllers to enable stable and efficient locomotion across diverse platforms. However…
A Unified and General Humanoid Whole-Body Controller for Versatile Locomotion
Yufei Xue, Wentao Dong, Minghuan Liu +2
Locomotion is a fundamental skill for humanoid robots. However, most existing works make locomotion a single, tedious, unextendable, and unconstrained movement. This limits the kin…