9 papers
XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representations
Shichao Fan, Kun Wu, Zhengping Che +12
Recent progress in large-scale robotic datasets and vision-language models (VLMs) has advanced research on vision-language-action (VLA) models. However, existing VLA models still f…
PDGS: Part-Level Decoupling and Continuous Deformation of Articulated Objects via Gaussian Splatting
Haowen Wang, Xiaoping Yuan, Zhao Jin +6
Articulated objects are ubiquitous and important in robotics, AR/VR, and digital twins. Most self-supervised methods for articulated object modeling reconstruct discrete interactio…
ArtVIP: Articulated Digital Assets of Visual Realism, Modular Interaction, and Physical Fidelity for Robot Learning
Zhao Jin, Zhengping Che, Tao Li +10
Robot learning increasingly relies on simulation to advance complex ability such as dexterous manipulations and precise interactions, necessitating high-quality digital assets to b…
RoboGene: Boosting VLA Pre-training via Diversity-Driven Agentic Framework for Real-World Task Generation
Yixue Zhang, Kun Wu, Zhi Gao +12
The pursuit of general-purpose robotic manipulation is hindered by the scarcity of diverse, real-world interaction data. Unlike data collection from web in vision or language, robo…
FreqPolicy: Efficient Flow-based Visuomotor Policy via Frequency Consistency
Yifei Su, Ning Liu, Dong Chen +6
Generative modeling-based visuomotor policies have been widely adopted in robotic manipulation, attributed to their ability to model multimodal action distributions. However, the h…
RoboAug: One Annotation to Hundreds of Scenes via Region-Contrastive Data Augmentation for Robotic Manipulation
Xinhua Wang, Kun Wu, Zhen Zhao +10
Enhancing the generalization capability of robotic learning to enable robots to operate effectively in diverse, unseen scenes is a fundamental and challenging problem. Existing app…