While Vision-Language-Action (VLA) models demonstrate impressive capabilities in robotic manipulation, their memoryless nature renders them brittle to test-time environment shifts, particularly hardware shifts caused by wear or imperfect calibration. Enabling these models to self-adapt during deployment without requiri...
Hong-Xin Zhang, Chun-Tse Lin, T. Wang et al.· 0 citations
Glove-based motion capture is emerging as a scalable approach to collecting dexterous-hand demonstration data. However, due to the kinematic gap between the human and robot hand, the recorded human motions cannot be executed directly on the robot, especially for contact-rich tool-use tasks involving in-hand reorientati...
Han Yang, Yian Wang, Yun-Long Song et al.· 0 citations
IM-ENGINE, a simulator-grounded pipeline that uses image editing as an intermediate representation for embodied data generation and a combination of generative semantic priors and simulator grounding enables scalable task-relevant supervision for robot learning.
Yian Wang, Jun-Yi Cao, Xiao-Wen Qiu et al.· 0 citations
GS-Agent is presented, an end-to-end multi-agent framework that integrates physics engines in the loop to generate realistic, dynamic, and controllable 4D physical worlds from natural language, envisioned as a foundation for a new paradigm in 4D world generation, empowering creative content creation and physical AI.
Hongxin Zhang, Chun-Tse Lin, Junyan Li et al.· arXiv.org· 1 citation
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