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Natural person-following behavior for social robots

Rachel Gockley, Jodi Forlizzi, Reid Simmons

Year
2007
Citations
291

Abstract

We are developing robots with socially appropriate spatial skills not only to travel around or near people, but also to accompany people side-by-side. As a step toward this goal, we are investigating the social perceptions of a robot's movement as it follows behind a person. This paper discusses our laser-based person-tracking method and two different approaches to person-following: direction-following and path-following. While both algorithms have similar characteristics in terms of tracking performance and following distances, participants in a pilot study rated the direction-following behavior as significantly more human-like and natural than the path-following behavior. We argue that the path-following method may still be more appropriate in some situations, and we propose that the ideal person-following behavior may be a hybrid approach, with the robot automatically selecting which method to use.

Keywords

RobotNatural (archaeology)Computer sciencePath (computing)PerceptionSocial robotTracking (education)Human–computer interactionMobile robotArtificial intelligence

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