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Human Intention Recognition for Safe Robot Action Planning Using Head Pose

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HCI International 2022 - Late Breaking Papers. Multimodality in Advanced Interaction Environments (HCII 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13519))

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Abstract

An efficient collaborative work between a person and technical system requires a deeper understanding of the human nature including social, cognitive, emotional or any other relationship that the person could have toward the technical system. Such relationships depend also on the case or specific knowledge about the current task they are performing together. Due to safety reasons, increased variability of new products, flexibility, and demands for defect-resistant production, a contemporary production lack such applications where people and robots operate together using social signals or contextual information.

The new paradigms that connect vision of Industry 4.0 with artificial intelligence, robotics, and computer networks are inevitably starting the new era of emerging ubiquitous production cells that will be used in factories of the future.

Authors propose an addition to a safety framework using a worker intention recognition with head pose information. As an indicator of intentions of a person in everyday communication, besides the experiences that represent a priori knowledge, humans are relying on social signals.

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Acknowledgements

This research is partially supported by Visage Technolgies AB and by the Croa-tian Science Foundation under the project “Affective Multimodal Interaction based on Constructed Robot Cognition—AMICORC (UIP-2020–02-7184)”.

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Authors and Affiliations

  1. Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Zagreb, Croatia

    Luka Orsag, Tomislav Stipancic, Leon Koren & Karlo Posavec

Authors
  1. Luka Orsag
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  2. Tomislav Stipancic
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  3. Leon Koren
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  4. Karlo Posavec
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Corresponding author

Correspondence to Luka Orsag .

Editor information

Editors and Affiliations

  1. The Open University of Japan, Chiba, Japan

    Masaaki Kurosu

  2. Tokyo University of Science, Tokyo, Saitama, Japan

    Sakae Yamamoto

  3. Tokyo City University, Tokyo, Japan

    Hirohiko Mori

  4. Soar Technology Inc., Orlando, FL, USA

    Dylan D. Schmorrow

  5. Katmai Government Services, Orlando, FL, USA

    Cali M. Fidopiastis

  6. Smart Future Initiative, Frankfurt am Main, Germany

    Norbert A. Streitz

  7. Kyushu University, Fukuoka, Japan

    Shin'ichi Konomi

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Orsag, L., Stipancic, T., Koren, L., Posavec, K. (2022). Human Intention Recognition for Safe Robot Action Planning Using Head Pose. In: Kurosu, M., et al. HCI International 2022 - Late Breaking Papers. Multimodality in Advanced Interaction Environments. HCII 2022. Lecture Notes in Computer Science, vol 13519. Springer, Cham. https://doi.org/10.1007/978-3-031-17618-0_23

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  • DOI: https://doi.org/10.1007/978-3-031-17618-0_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-17617-3

  • Online ISBN: 978-3-031-17618-0

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