A context-dependent attention system for a social robot

  • Authors:
  • Cynthia Breazeal;Brian Scassellati

  • Affiliations:
  • MIT Artificial Intelligence Lab, Cambridge, MA;MIT Artificial Intelligence Lab, Cambridge, MA

  • Venue:
  • IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
  • Year:
  • 1999

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Abstract

This paper presents part of an on-going project to integrate perception, attention, drives, emotions, behavior arbitration, and expressive acts for a robot designed to interact socially with humans. We present the design of a visual attention system based on a model of human visual search behavior from Wolfe (1994). The attention system integrates perceptions (motion detection, color saliency, and face popouts) with habituation effects and influences from the robot's motivational and behavioral state to create a context-dependent attention activation map. This activation map is used to direct eye movements and to satiate the drives of the motivational system.