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Social navigation model based on human intention analysis using face orientation

Photchara Ratsamee, Yasushi Mae, Kenichi Ohara, Masaru Kojima, Tatsuo Arai

Year
2013
Citations
33

Abstract

We propose a social navigation model that allows a robot to navigate in a human environment according to human intentions, in particular during a situation where the human encounters a robot and he/she wants to avoid, unavoid (maintain his/her course), or approach the robot. Avoiding, unavoiding, and approaching trajectories of humans are classified based on the face orientation on a social force model and their predicted motion. The proposed model is developed based on human motion and behavior (especially face orientation and overlapping personal space) analysis in preliminary experiments. Our experimental evidence demonstrates that the robot is able to adapt its motion by preserving personal distance from passers-by, and approaching persons who want to interact with the robot. This work contributes to the future development of a human-robot socialization environment.

Keywords

Orientation (vector space)RobotComputer scienceMotion (physics)Face (sociological concept)Human–computer interactionArtificial intelligenceSocializationSocial force modelComputer vision

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