Mobile humanoid manipulation requires both reaching a usable workspace and preserving precise hand-object interactions as object poses and contact conditions change. Learning these behaviors from limited task-specific data remains challenging. To bridge this gap, we introduce Praxis, a whole-body manipulation framework...
Shu-Liang He, Rui-Yang Xu, Bo Yue et al.· 0 citations
This work presents RoboReact, a framework that automatically synthesizes whole-body humanoid manipulation skills from a single egocentric RGB-D observation, and highlights the potential of combining generative models, vision-language reasoning, and closed-loop control for scalable humanoid skill acquisition.
Shu-Liang He, Shuai Wang, Bo Yue et al.· 3 citations· ⚡1
Developing autonomous hydraulic excavators is constrained by limited access to physical machines and the high cost of real-world experimentation. This paper proposes a simulation-to-real framework for learning a system-level digital surrogate using Long Short-Term Memory (LSTM) networks. Instead of modeling internal dy...
Shuai-Tong Wang, Shen Wang, Qiang Wang et al.· 0 citations
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