Learning Visual Robotic Control Efficiently with Contrastive Pre-training and Data Augmentation
Albert Zhan,Ruihan Zhao,Lerrel Pinto,Pieter Abbeel,Michael Laskin,Albert Zhan,Ruihan Zhao,Lerrel Pinto,Pieter Abbeel,Michael Laskin
Recent advances in unsupervised representation learning significantly improved the sample efficiency of training Reinforcement Learning policies in simulated environments. However, similar gains have not yet been seen for real-robot reinforcement learning. In this work, we focus on enabling data-efficient real-robot learning from pixels. We present Contrastive Pre-training and Data Augmentation fo...
