Publications (8)
Being-H0.7: A Latent World-Action Model from Egocentric Videos
Hao Luo, Wanpeng Zhang, Yicheng Feng +6
Visual-Language-Action models (VLAs) have advanced generalist robot control by mapping multimodal observations and language instructions directly to actions, but sparse action supe…
RealDexUMI: A Wearable Universal Manipulation Interface for Dexterous Robot Learning
Chaoyi Xu, Yixuan Jiang, Jiahui Huan +7
Learning dexterous manipulation requires demonstrations that preserve fine hand-object interactions while remaining executable at deployment. Existing pipelines either lose deploya…
Cross-Embodiment Dexterous Grasping with Reinforcement Learning
Haoqi Yuan, Bohan Zhou, Yuhui Fu +1
Dexterous hands exhibit significant potential for complex real-world grasping tasks. While recent studies have primarily focused on learning policies for specific robotic hands, th…
Learning Diverse Bimanual Dexterous Manipulation Skills from Human Demonstrations
Bohan Zhou, Haoqi Yuan, Yuhui Fu +1
Bimanual dexterous manipulation is a critical yet underexplored area in robotics. Its high-dimensional action space and inherent task complexity present significant challenges for…
Efficient Residual Learning with Mixture-of-Experts for Universal Dexterous Grasping
Ziye Huang, Haoqi Yuan, Yuhui Fu +1
Universal dexterous grasping across diverse objects presents a fundamental yet formidable challenge in robot learning. Existing approaches using reinforcement learning (RL) to deve…
Creative Agents: Empowering Agents with Imagination for Creative Tasks
Penglin Cai, Chi Zhang, Yuhui Fu +2
We study building embodied agents for open-ended creative tasks. While existing methods build instruction-following agents that can perform diverse open-ended tasks, none of them d…