Human intention recognition is one of the most important research areas in the human-robot interaction in order to accomplish more natural and intelligent interaction. In the public service area, the basic four human intentional actions, 'approach', 'depart', 'bypass', and 'stop' were investigated by the human's movement pattern. In order to recognize those four human intentional actions, the mobile robot measured 360 degree distance between a robot and a human by two IR-scanner sensors, and three problems were solved: 1) human detection and tracking by improved K-means clustering method, 2) absolute human velocity estimation by Extended Kalman Filter, and 3) inferring intentional actions by HMM with position-dependent observation model. The result showed as quite good performance that inferred the probabilities of those four intentional actions.
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