Improving People Awareness of Service Robots by Semantic Scene Knowledge
Many mobile service robots operate in close interaction with humans. Being constantly aware of the people in the surrounding of the robot thus poses an important challenge to perception and behavior design.
In this paper, we present an approach to people awareness for mobile service robots that utilizes knowledge about the semantics of the environment. The known semantics, e.g., about walkable floor, chairs, and shelves, provides the robot with prior information. We utilize information about the a-priori likelihood that people are present at semantically distinct places. Together with reasonable face heights inferred from scene semantics, this information supports robust detection and awareness of people in the robot’s environment. For efficient exploration of the environment for people, we propose a strategy which chooses search locations that maximize the expected detection rate of new persons.
We evaluate our approach with our domestic service robot that competes in the RoboCup@Home league.
KeywordsService Robot False Positive Detection Face Height Presence Probability Laser Range Scan
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