5 papers
RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation
Shihan Wu, Xuecheng Liu, Shaoxuan Xie +81
Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due to the significant hardware hete…
AoE: Always-on Egocentric Human Video Collection for Embodied AI
Bowen Yang, Zishuo Li, Yang Sun +15
Embodied foundation models require large-scale, high-quality real-world interaction data for pre-training and scaling. However, existing data collection methods suffer from high in…
METIS: Multi-Source Egocentric Training for Integrated Dexterous Vision-Language-Action Model
Yankai Fu, Ning Chen, Junkai Zhao +5
Building a generalist robot that can perceive, reason, and act across diverse tasks remains an open challenge, especially for dexterous manipulation. A major bottleneck lies in the…
RoboOS-NeXT: A Unified Memory-based Framework for Lifelong, Scalable, and Robust Multi-Robot Collaboration
Huajie Tan, Cheng Chi, Xiansheng Chen +21
The proliferation of collaborative robots across diverse tasks and embodiments presents a central challenge: achieving lifelong adaptability, scalable coordination, and robust sche…
RoboBrain 2.0 Technical Report
BAAI RoboBrain Team, Mingyu Cao, Huajie Tan +50
We introduce RoboBrain 2.0, our latest generation of embodied vision-language foundation models, designed to unify perception, reasoning, and planning for complex embodied tasks in…