73 citations · 162 across the 20 of their papers we have counts for
4 papers · 1 filter
Learning Language-Conditioned Deformable Object Manipulation with Graph Dynamics
Yuhong Deng, Kai Mo, Chongkun Xia +1
Multi-task learning of deformable object manipulation is a challenging problem in robot manipulation. Most previous works address this problem in a goal-conditioned way and adapt g…
Deep Reinforcement Learning Based on Local GNN for Goal-conditioned Deformable Object Rearranging
Yuhong Deng, Chongkun Xia, Xueqian Wang +1
Object rearranging is one of the most common deformable manipulation tasks, where the robot needs to rearrange a deformable object into a goal configuration. Previous studies focus…
Graph-Transporter: A Graph-based Learning Method for Goal-Conditioned Deformable Object Rearranging Task
Yuhong Deng, Chongkun Xia, Xueqian Wang +1
Rearranging deformable objects is a long-standing challenge in robotic manipulation for the high dimensionality of configuration space and the complex dynamics of deformable object…
Visual-tactile Fusion for Transparent Object Grasping in Complex Backgrounds
Shoujie Li, Haixin Yu, Wenbo Ding +5
The accurate detection and grasping of transparent objects are challenging but of significance to robots. Here, a visual-tactile fusion framework for transparent object grasping un…