6 papers
DynamicWAM: Dual-Path Motion Conditioning for World-Action Models in Dynamic Manipulation
Yunfan Lou, Hewen Gao, Xiyu Zhu +6
Dynamic manipulation requires robots to infer target motion and respond promptly, yet existing World-Action Models (WAMs) typically condition only on the current frame and execute…
Data Pyramid for Embodied Manipulation: A Survey
Yifan Ye, Yankai Fu, Yaoxu Lv +26
Multimodal foundation models learned to see and to speak by consuming the whole internet. Embodied agents admit no such shortcut, since they require data that couple observations w…
Mitigating Gradient Pathology in PINNs through Aligned Constraint
Yichen Luo, Peiyu Zhu, Dongxiao Hu +5
While Physics-Informed Neural Networks (PINNs) are powerful for solving Partial Differential Equations (PDEs), their training is often paralyzed by gradient pathology. The gradient…
Transferring Vision-Language-Action Models to Industry Applications: Architectures, Performance, and Challenges
Shuai Li, Chen Yizhe, Li Dong +4
The application of artificial intelligence (AI) in industry is accelerating the shift from traditional automation to intelligent systems with perception and cognition. Vision langu…
Liaohe-CobotMagic-PnP: an Imitation Learning Dataset of Intelligent Robot for Industrial Applications
Chen Yizhe, Wang Qi, Hu Dongxiao +10
In Industry 4.0 applications, dynamic environmental interference induces highly nonlinear and strongly coupled interactions between the environmental state and robotic behavior. Ef…
MMET: A Multi-Input and Multi-Scale Transformer for Efficient PDEs Solving
Yichen Luo, Jia Wang, Dapeng Lan +2
Partial Differential Equations (PDEs) are fundamental for modeling physical systems, yet solving them in a generic and efficient manner using machine learning-based approaches rema…