Conditional StyleGAN for Grasp Generation
Florian Patzelt,Robert Haschke,Helge Ritter,Florian Patzelt,Robert Haschke,Helge Ritter
We present an approach based on conditional generative adversarial networks (GANs) to generate grasps directly and in a feed-forward manner from a raw depth image input. Building on the recently introduced StyleGAN architecture we extend results from an earlier proof-of-concept paper [1] and demonstrate successful sim2real transfer of grasp outputs for a robot arm with a Shadow Dexterous Hand. We ...
