5 citations · 12 across the 17 of their papers we have counts for
4 papers · 1 filter
ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation
Xiaoqi Li, Mingxu Zhang, Yiran Geng +6
Robot manipulation relies on accurately predicting contact points and end-effector directions to ensure successful operation. However, learning-based robot manipulation, trained on…
Learning Part Motion of Articulated Objects Using Spatially Continuous Neural Implicit Representations
Yushi Du, Ruihai Wu, Yan Shen +1
Articulated objects (e.g., doors and drawers) exist everywhere in our life. Different from rigid objects, articulated objects have higher degrees of freedom and are rich in geometr…
ImageManip: Image-based Robotic Manipulation with Affordance-guided Next View Selection
Xiaoqi Li, Yanzi Wang, Yan Shen +6
In the realm of future home-assistant robots, 3D articulated object manipulation is essential for enabling robots to interact with their environment. Many existing studies make use…
Learning Environment-Aware Affordance for 3D Articulated Object Manipulation under Occlusions
Ruihai Wu, Kai Cheng, Yan Shen +3
Perceiving and manipulating 3D articulated objects in diverse environments is essential for home-assistant robots. Recent studies have shown that point-level affordance provides ac…