Learning a Generative Transition Model for Uncertainty-Aware Robotic Manipulation
Lars Berscheid,Pascal Meißner,Torsten Kröger,Lars Berscheid,Pascal Meißner,Torsten Kröger
Robot learning of real-world manipulation tasks remains challenging and time consuming, even though actions are often simplified by single-step manipulation primitives. In order to compensate the removed time dependency, we additionally learn an image-to-image transition model that is able to predict a next state including its uncertainty. We apply this approach to bin picking, the task of emptyin...
