A Unified Framework for Human-Robot Knowledge Transfer

Transferring knowledge is a vital skill between humans for efficiently learning a new concept. In a perfect system, a human demonstrator can teach a robot a new task by using natural language and physical gestures. The robot would gradually accumulate and refine its spatial, temporal, and causal understanding of the world. The knowledge can then be transferred back to another human, or further to another robot. The implications of effective human to robot knowledge transfer include the compelling opportunity of a robot acting as the teacher, guiding humans in new tasks. The technical difficulty in achieving a robot implementation Figure 1: The robot autonomously performs a cloth folding of this caliber involves both an expressive knowledge task after learning from a human demonstration.