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Towards Crossmodal Learning for Smooth Multimodal Attention Orientation

  • Frederik Haarslev
  • David Docherty
  • Stefan-Daniel Suvei
  • William Kristian Juel
  • Leon BodenhagenEmail author
  • Danish Shaikh
  • Norbert Krüger
  • Poramate Manoonpong
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11357)

Abstract

Orienting attention towards another person of interest is a fundamental social behaviour prevalent in human-human interaction and crucial in human-robot interaction. This orientation behaviour is often governed by the received audio-visual stimuli. We present an adaptive neural circuit for multisensory attention orientation that combines auditory and visual directional cues. The circuit learns to integrate sound direction cues, extracted via a model of the peripheral auditory system of lizards, with visual directional cues via deep learning based object detection. We implement the neural circuit on a robot and demonstrate that integrating multisensory information via the circuit generates appropriate motor velocity commands that control the robot’s orientation movements. We experimentally validate the adaptive neural circuit for co-located human target and a loudspeaker emitting a fixed tone.

Keywords

Sensor fusion Neural control Human robot interaction 

Notes

Acknowledgement

This research was part of the SMOOTH project (project number 6158-00009B) by Innovation Fund Denmark.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Frederik Haarslev
    • 1
  • David Docherty
    • 2
  • Stefan-Daniel Suvei
    • 1
  • William Kristian Juel
    • 1
  • Leon Bodenhagen
    • 1
    Email author
  • Danish Shaikh
    • 2
  • Norbert Krüger
    • 1
  • Poramate Manoonpong
    • 2
    • 3
  1. 1.SDU Robotics, Maersk Mc-Kinney Moller InstituteUniversity of Southern DenmarkOdenseDenmark
  2. 2.SDU Embodied Systems for Robotics and Learning, Maersk Mc-Kinney Moller InstituteUniversity of Southern DenmarkOdenseDenmark
  3. 3.Bio-inspired Robotics and Neural Engineering Laboratory, School of Information Science and TechnologyVidyasirimedhi Institute of Science and TechnologyWangchanThailand

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