Towards More Generalizable One-shot Visual Imitation Learning
Zhao Mandi,Fangchen Liu,Kimin Lee,Pieter Abbeel,Zhao Mandi,Fangchen Liu,Kimin Lee,Pieter Abbeel
A general-purpose robot should be able to master a wide range of tasks and quickly learn a novel one by leveraging past experiences. One-shot imitation learning (OSIL) approaches this goal by training an agent with (pairs of) expert demonstrations, such that at test time, it can directly execute a new task from just one demonstration. However, so far this framework has been limited to training on ...
