Using spatial context knowledge in gesture recognition for commanding a domestic service robot

Abstract

The use of human gestures for interacting with robot systems in domestic environments is investigated. Special attention is paid to the recognition of the user's intent behind a gestural action. The main advantage of our approach is that the human's movement together with valuable information extracted from a spatial scene representation are directly considered while trying to uncover the intention behind a human's gesture. To uncover the intention of dynamic human gestures we use continuous density hidden Markov models. As an application example, instructing a domestic service robot is considered. An event driven control architecture permits easy context switching and meets the demands of an interactive robot assistant.