4 papers
VT-MUSE: Multimodal Unified Sequential Visuotactile Representation Learning for Manipulation
Congsheng Xu, Qiaochu Yang, Fangyuan Shi +9
We propose VT-MUSE, a Multimodal Unified SEquential representation learning framework for visuotactilemanipulation. Existing approaches often encode visual and tactile observations…
ExoGS: A 4D Real-to-Sim-to-Real Framework for Scalable Manipulation Data Collection
Yiming Wang, Ruogu Zhang, Minyang Li +7
Real-to-Sim-to-Real technique is gaining increasing interest for robotic manipulation, as it can generate scalable data in simulation while having narrower sim-to-real gap. However…
AirExo-2: Scaling up Generalizable Robotic Imitation Learning with Low-Cost Exoskeletons
Hongjie Fang, Chenxi Wang, Yiming Wang +11
Scaling up robotic imitation learning for real-world applications requires efficient and scalable demonstration collection methods. While teleoperation is effective, it depends on…
ForceMimic: Force-Centric Imitation Learning with Force-Motion Capture System for Contact-Rich Manipulation
Wenhai Liu, Junbo Wang, Yiming Wang +2
In most contact-rich manipulation tasks, humans apply time-varying forces to the target object, compensating for inaccuracies in the vision-guided hand trajectory. However, current…