8 papers
ForceBench: Benchmarking Force Integration for Robotic Manipulation
Xuan Han, Zinuo Jin, Tianlin Li +8
Force feedback provides vision-language-action (VLA) policies with physical observations that can guide action selection and execution. However, differences in tasks, demonstration…
Achieve What You Imagined: Learning to Align Actions with Visual Plans
Yuheng Qiao, Ziran Wei, Xiaohan Wang +5
World-action models can jointly predict future visual observations and robot actions. However, discrepancies may exist between their visual predictions and the consequences implied…
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…
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…
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…