Robot Learning of 6 DoF Grasping using Model-based Adaptive Primitives
Lars Berscheid,Christian Friedrich,Torsten Kröger,Lars Berscheid,Christian Friedrich,Torsten Kröger
Robot learning is often simplified to planar manipulation due to its data consumption. Then, a common approach is to use a fully-convolutional neural network (FCNN) to estimate the reward of grasp primitives. In this work, we extend this approach by parametrizing the two remaining, lateral degrees of freedom (DoFs) of the primitives. We apply this principle to the task of 6 DoF bin picking: We int...
