AAAI 2026technical0 citations

GraphGrasp: Lightweight and Efficient Graph-Guided 6-DoF Robotic Grasp Pose Estimation Network

Sheng Yu, Di-Hua Zhai, Yuanqing Xia

Abstract

6-DoF object grasping is a crucial skill for embodied intelligent robots. Previous methods often rely on large-scale networks for feature extraction, followed by grasp pose prediction, which increases the network

BibTeX
@inproceedings{aaai2026_graphgrasplightw,
  title = {GraphGrasp: Lightweight and Efficient Graph-Guided 6-DoF Robotic Grasp Pose Estimation Network},
  author = {Sheng Yu and Di-Hua Zhai and Yuanqing Xia},
  booktitle = {AAAI 2026},
  year = {2026}
}
GraphGrasp: Lightweight and Efficient Graph-Guided 6-DoF Robotic Grasp Pose Estimation Network · AAAI 2026