1 citations · 1 across the 5 of their papers we have counts for
5 papers
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…
RPMArt: Towards Robust Perception and Manipulation for Articulated Objects
Junbo Wang, Wenhai Liu, Qiaojun Yu +4
Articulated objects are commonly found in daily life. It is essential that robots can exhibit robust perception and manipulation skills for articulated objects in real-world roboti…
GAMMA: Generalizable Articulation Modeling and Manipulation for Articulated Objects
Qiaojun Yu, Junbo Wang, Wenhai Liu +5
Articulated objects like cabinets and doors are widespread in daily life. However, directly manipulating 3D articulated objects is challenging because they have diverse geometrical…