4 papers
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…
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…