Robots Learn Actions and Cooperative Tasks by Imitation.

Imitation learning, which involves a robot observing and copying a human demonstrator, empowers a robot to "learn" new actions, and thus improve robot performance in tasks that require human-robot collaboration (HRC). We formulate a latent space representation of observed behaviors, and associate this representation with the corresponding one for target robotic behaviors. Effectively, a mapping of observed to reproduced actions is devised that abstracts action variations and differences between the human and robotic manipulators.