most citedDeep Reinforcement Learning Based on Local GNN for Goal-conditioned Deformable Object Rearranging

15 citations · 22 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CV2024★ 1 cited

SD-Net: Symmetric-Aware Keypoint Prediction and Domain Adaptation for 6D Pose Estimation In Bin-picking Scenarios

Ding-Tao Huang, En-Te Lin, Lipeng Chen +2

Despite the success in 6D pose estimation in bin-picking scenarios, existing methods still struggle to produce accurate prediction results for symmetry objects and real world scena…

cs.RO2023★ 15 cited

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…

cs.RO2023★ 6 cited

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…