6 papers · 1 filter
WM-VS: Progress-Aligned World Models for Closed-Loop Visual Servoing
Guanzhong Sun, Junyi Ma, Yixuan Zhou +3
Closed-loop visual servoing requires predictions that indicate whether an action reduces task error, not only whether the action is plausible. We call this gap the prediction-contr…
When would Vision-Proprioception Policies Fail in Robotic Manipulation?
Jingxian Lu, Wenke Xia, Yuxuan Wu +2
Proprioceptive information is critical for precise servo control by providing real-time robotic states. Its collaboration with vision is highly expected to enhance performances of…
Continually Evolving Skill Knowledge in Vision Language Action Model
Yuxuan Wu, Guangming Wang, Zhiheng Yang +4
Vision-language-action (VLA) models show promising knowledge accumulation ability through pretraining, yet continual learning remains challenging. Existing continual imitation lear…
TrajBooster: Boosting Humanoid Whole-Body Manipulation via Trajectory-Centric Learning
Jiacheng Liu, Pengxiang Ding, Qihang Zhou +8
Recent Vision-Language-Action models show potential to generalize across embodiments but struggle to quickly align with a new robot's action space when high-quality demonstrations…
SymBridge: A Human-in-the-Loop Cyber-Physical Interactive System for Adaptive Human-Robot Symbiosis
Haoran Chen, Yiteng Xu, Yiming Ren +14
The development of intelligent robots seeks to seamlessly integrate them into the human world, providing assistance and companionship in daily life and work, with the ultimate goal…
RL-GSBridge: 3D Gaussian Splatting Based Real2Sim2Real Method for Robotic Manipulation Learning
Yuxuan Wu, Lei Pan, Wenhua Wu +4
Sim-to-Real refers to the process of transferring policies learned in simulation to the real world, which is crucial for achieving practical robotics applications. However, recent…