Good in Bad (GiB): Sifting Through End-user Demonstrations for Learning a Better Policy

Imitation learning offers a promising framework for enabling robots to acquire diverse skills from human users. However, most imitation learning algorithms assume access to high-quality demonstrations an unrealistic expectation when collecting data from non-expert users, whose demonstrations often c