Scoring Graspability based on Grasp Regression for Better Grasp Prediction
Amaury Depierre Emmanuel Dellandréa Liming Chen Amaury Depierre Emmanuel Dellandréa Liming Chen
Grasping objects is one of the most important abilities that a robot needs to master in order to interact with its environment. Current state-of-the-art methods rely on deep neural networks trained to jointly predict a graspability score together with a regression of an offset with respect to grasp reference parameters. However, these two predictions are performed independently, which can lead to ...