In contact-rich manipulation, actions that appear equally plausible from vision can produce different contact outcomes, while reactive control based on current tactile feedback may respond too late to prevent failure. We present ForeTac, a predictive contact-guidance framework organized as a represent-predict-evaluate-...
Zhi-Yuan Chen, Shuai Chen, Hao-Ran Zhou et al.· 0 citations
Finding the object referred to by language in a partially observed 3D scene is a core capability for embodied agents. Existing approaches either couple object search with online exploration, which can be costly when relevant observations have already been captured, or query pre-built open-vocabulary maps and scene grap...
Shi-Xiong Xu, Zhi-Yuan Chen, Song Ding et al.· 0 citations
A large language model-assisted distillation–fusion framework (VERLADF) is proposed, which introduces emotion instruction data generated by GPT to fine-tune a VLM, thereby enhancing its emotional semantic understanding capability and adaptively fuses predictions from the instruction-tuned VLM and the distillation modul...
UCAG-P is introduced, a camera-centric unified action formulation that structurally aligns heterogeneous embodied datasets into a shared geometric action space, and allows a shared VLA policy to learn transferable manipulation geometry while retaining embodiment-specific controllability.
Xiaomi Embodied Intelligence Team, University of Macau Shaoqing Xu, Fang Li et al.· 0 citations
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