4 papers
GEM: Generative Supervision Helps Embodied Intelligence
Ruowen Zhao, Bangguo Li, Zuyan Liu +9
Embodied Vision-Language Models (VLMs) have demonstrated impressive performance and generalization in robotics, particularly within Vision-Language-Action frameworks. However, a si…
RDT2: Exploring the Scaling Limit of UMI Data Towards Zero-Shot Cross-Embodiment Generalization
Songming Liu, Bangguo Li, Kai Ma +5
Vision-Language-Action (VLA) models hold promise for generalist robotics but currently struggle with data scarcity, architectural inefficiencies, and the inability to generalize ac…
RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation
Songming Liu, Lingxuan Wu, Bangguo Li +6
Bimanual manipulation is essential in robotics, yet developing foundation models is extremely challenging due to the inherent complexity of coordinating two robot arms (leading to…
An Atomic Skill Library Construction Method for Data-Efficient Embodied Manipulation
Dongjiang Li, Bo Peng, Chang Li +13
Embodied manipulation is a fundamental ability in the realm of embodied artificial intelligence. Although current embodied manipulation models show certain generalizations in speci…