Edge Grasp Network: A Graph-Based SE(3)-invariant Approach to Grasp Detection

Haojie Huang, Dian Wang, Xupeng Zhu, Robin Walters, Robert Platt

Keywords: SE(3) Equivariance, Grasping, Manipulation, Graph Neural Network, Deep Learning

Abstract: Given point cloud input, the problem of 6-DoF grasp pose detection is to identify a set of hand poses in $\SE(3)$ from which an object can be successfully grasped. This important problem has many practical applications. Here we propose a novel method and neural network model that enables better grasp success rates relative to what is available in the literature. The method takes standard point cloud data as input and works well with single-view point clouds observed from arbitrary viewing directions. Videos and code are available at \url{https://haojhuang.github.io/edge_grasp_page/}.

Community Implementations: [ 2 code implementations](https://www.catalyzex.com/paper/edge-grasp-network-a-graph-based-se-invariant/code)