4 citations · 5 across the 6 of their papers we have counts for
6 papers
AMO: Adaptive Motion Optimization for Hyper-Dexterous Humanoid Whole-Body Control
Jialong Li, Xuxin Cheng, Tianshu Huang +3
Humanoid robots derive much of their dexterity from hyper-dexterous whole-body movements, enabling tasks that require a large operational workspace: such as picking objects off the…
Humanoid Policy ~ Human Policy
Ri-Zhao Qiu, Shiqi Yang, Xuxin Cheng +12
Training manipulation policies for humanoid robots with diverse data enhances their robustness and generalization across tasks and platforms. However, learning solely from robot de…
ExBody2: Advanced Expressive Humanoid Whole-Body Control
Mazeyu Ji, Xuanbin Peng, Fangchen Liu +4
This paper tackles the challenge of enabling real-world humanoid robots to perform expressive and dynamic whole-body motions while maintaining overall stability and robustness. We…
Mobile-TeleVision: Predictive Motion Priors for Humanoid Whole-Body Control
Chenhao Lu, Xuxin Cheng, Jialong Li +6
Humanoid robots require both robust lower-body locomotion and precise upper-body manipulation. While recent Reinforcement Learning (RL) approaches provide whole-body loco-manipulat…
ACE: A Cross-Platform Visual-Exoskeletons System for Low-Cost Dexterous Teleoperation
Shiqi Yang, Minghuan Liu, Yuzhe Qin +6
Learning from demonstrations has shown to be an effective approach to robotic manipulation, especially with the recently collected large-scale robot data with teleoperation systems…
Open-TeleVision: Teleoperation with Immersive Active Visual Feedback
Xuxin Cheng, Jialong Li, Shiqi Yang +2
Teleoperation serves as a powerful method for collecting on-robot data essential for robot learning from demonstrations. The intuitiveness and ease of use of the teleoperation syst…