Towards human-robot coordination: skill modeling and transferring via hidden Markov model

Abstract

Automatic modeling and transferring human skill to a robot is an important step towards creating an intelligent robot in a cooperative environment where humans and robots can complement and enhance each other's performance in a reciprocal manner. We first classify two distinct categories of skills, i.e., action skill and reaction skill. Then we address how the hidden Markov model can be used for modeling these two types of human skill. We focus on the reaction learning scheme and discuss the issues and problems associated with the hidden Markov model approach.