Robot Fine-Tuning Made Easy: Pre-Training Rewards and Policies for Autonomous Real-World Reinforcement Learning
Jingyun Yang,Max Sobol Mark,Brandon Vu,Archit Sharma,Jeannette Bohg,Chelsea Finn,Jingyun Yang,Max Sobol Mark,Brandon Vu,Archit Sharma,Jeannette Bohg,Chelsea Finn
The pre-train and fine-tune paradigm in machine learning has had dramatic success in a wide range of domains because the use of existing data or pre-trained models on the internet enables quick and easy learning of new tasks. We aim to enable this paradigm in robotic reinforcement learning, allowing a robot to learn a new task with little human effort by leveraging data and models from the Interne...
