8 papers
ACE-F: A Cross Embodiment Foldable System with Force Feedback for Dexterous Teleoperation
Rui Yan, Jiajian Fu, Shiqi Yang +3
Teleoperation systems are essential for efficiently collecting diverse and high-quality robot demonstration data, especially for complex, contact-rich tasks. However, current teleo…
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…
ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training
Ge Yan, Jiyue Zhu, Yuquan Deng +8
This paper introduces ManiFlow, a visuomotor imitation learning policy for general robot manipulation that generates precise, high-dimensional actions conditioned on diverse visual…
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…
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…