4 papers
Adaptive Scaling of Policy Constraints for Offline Reinforcement Learning
Tan Jing, Xiaorui Li, Chao Yao +4
Offline reinforcement learning (RL) enables learning effective policies from fixed datasets without any environment interaction. Existing methods typically employ policy constraint…
Iterative Closed-Loop Motion Synthesis for Scaling the Capabilities of Humanoid Control
Weisheng Xu, Qiwei Wu, Jiaxi Zhang +7
Physics-based humanoid control relies on training with motion datasets that have diverse data distributions. However, the fixed difficulty distribution of datasets limits the perfo…
HERO: Hierarchical Traversable 3D Scene Graphs for Embodied Navigation Among Movable Obstacles
Yunheng Wang, Yixiao Feng, Yuetong Fang +5
3D Scene Graphs (3DSGs) constitute a powerful representation of the physical world, distinguished by their abilities to explicitly model the complex spatial, semantic, and function…
FARM: Frame-Accelerated Augmentation and Residual Mixture-of-Experts for Physics-Based High-Dynamic Humanoid Control
Tan Jing, Shiting Chen, Yangfan Li +2
Unified physics-based humanoid controllers are pivotal for robotics and character animation, yet models that excel on gentle, everyday motions still stumble on explosive actions, h…