Meta-Reinforcement Learning for Robotic Industrial Insertion Tasks
Gerrit Schoettler,Ashvin Nair,Juan Aparicio Ojea,Sergey Levine,Eugen Solowjow,Gerrit Schoettler,Ashvin Nair,Juan Aparicio Ojea,Sergey Levine,Eugen Solowjow
Robotic insertion tasks are characterized by contact and friction mechanics, making them challenging for conventional feedback control methods due to unmodeled physical effects. Reinforcement learning (RL) is a promising approach for learning control policies in such settings. However, RL can be unsafe during exploration and might require a large amount of real-world training data, which is expens...
