Physical contact often determines how a humanoid should respond during loco-manipulation, yet vision and proprioception alone are often insufficient to characterize physical interaction, especially when the contact region is occluded. Unlike sparse force or torque measurements at predefined regions, distributed tactile...
Zi-Hao Wang, Shu-Tong Liu, Si-Qi Zheng et al.· 0 citations
This is the first real-world humanoid racket-sport system to demonstrate multi-skill human--robot rallies including highly dynamic jump returns, and is the first real-world humanoid racket-sport system to demonstrate multi-skill human--robot rallies including highly dynamic jump returns.
Jing-Zhi Cui, Zhe-Xiong Wang, Bang-Jie Xu et al.· 0 citations
Long-horizon robot manipulation reuses skills across many task compositions, but improving these compositions with additional end-to-end demonstrations is costly. A practical self-improving system must decide both what to teach next and where to apply that supervision. We present ROBOCOACH, a world-model-guided coachin...
Jia-Jun Liu, Yi-Fan Chen, Yi-Chao Liu et al.· 0 citations
Weave is presented, a unified framework for learning whole-body dexterous humanoid-object interaction from captured human demonstrations that converts captured human-object interactions into executable robot-object references through contact-aware retargeting and approach-motion completion.
Liu Cao, Xing-Ze Wu, Jing-Zhi Cui et al.· 2 citations
It is shown that routine clinic images can be transformed into operational digital twins for task-based evaluation of embodied AI, establishing operational validity as a key principle for clinical digital twins and providing an intermediate layer between offline development and physical deployment of embodied AI in hea...
Xinyuan Wu, Jingrao Zhang, Meng-Di Xu et al.· 0 citations
Experiments in both simulation and real-world settings demonstrate that R2S-Eval produces reliable and stable policy conclusions, achieves agreement with human preferences, substantially reduces repeated hardware-operation effort, and reveals behavior-quality differences that are not captured by binary success labels.
Yi-Di Wang, Fei-Xiang Ruan, Ruo-Qu Chen et al.· 2 citations
It is argued that clinical autonomy is developing in stages from clinician‐supervised imaging and decision support to bounded robotic subtasks and workflow‐level coordination, instead of through unsupervised replacement of healthcare professionals.
