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GraNet: A Multi-Level Graph Network for 6-DoF Grasp Pose Generation in Cluttered Scenes

Description

6-DoF object-agnostic grasping in unstructured environments is a critical yet challenging task in robotics. Most current works use non-optimized approaches to sample grasp locations and learn spatial features without concerning the grasping task. This paper proposes GraNet, a graph-based grasp pose generation framework that translates a point cloud scene into multi-level graphs and propagates features through graph neural networks. By building graphs at the scene level, object level, and grasp p

Source

http://arxiv.org/abs/2312.03345v1