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International Conference on Social Robotics

ICSR 2021: Social Robotics pp 329–338Cite as

Autonomous Group Detection, Delineation, and Selection for Human-Agent Interaction

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13086))

Abstract

If a human and a robot team need to approach a specific group to make an announcement or delivery, how will the human describe which group to approach, and how will the robot approach the group? The robots will need to take a relatively arbitrary description of a group, identify that group from onboard sensors, and accurately approach the correct group. This task requires the robot to reason over and delineate individuals and groups from other individuals and groups. We ran a study on how people describe groups for delineation and identified the features most likely used by a person. We then present a framework that allows for an agent to detect, delineate, and select a given social group from the context of a description. We also present a group detection algorithm that works on a mobile platform in real-time and provide a formalization for a Group Selection Problem.

This research was performed while BW held an NRC Research Associateship award at NRL. This research was funded by ONR and OSD to GT.

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Notes

  1. 1.

    https://www.vyond.com/.

  2. 2.

    A linear effects mixed model shows a similar result while taking into account the multiple random effects. A later report will provide a fuller description.

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Acknowledgements

The views, opinions and/or findings expressed are those of the authors and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government. The authors would like to thank Magda Bugajska and Bill Adams in their thoughts on combining the detection to representation on robotic platforms.

Author information

Authors and Affiliations

  1. NRC Postdoctoral Associate, US Naval Research Laboratory, Washington, D.C., USA

    Ben Wright

  2. Peraton, Washington, D.C., USA

    J. Malcolm McCurry

  3. Navy Center for Applied Research in Artificial Intelligence, US Naval Research Laboratory, Washington, D.C., USA

    Wallace Lawson & J. Gregory Trafton

Authors
  1. Ben Wright
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  2. J. Malcolm McCurry
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  3. Wallace Lawson
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  4. J. Gregory Trafton
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Corresponding author

Correspondence to Ben Wright .

Editor information

Editors and Affiliations

  1. Department of Electronic and Communication Engineering, National University of Singapore, Faculty of Engineering, Singapore, Singapore

    Haizhou Li

  2. The National University of Singapore, Singapore, Singapore

    Shuzhi Sam Ge

  3. A*STAR Institute for Infocomm Research, Singapore, Singapore

    Yan Wu

  4. Center for Human Technologies, Istituto Italiano Tecnologia, Genoa, Italy

    Agnieszka Wykowska

  5. Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA

    Hongsheng He

  6. Qingdao University, Qingdao, China

    Xiaorui Liu

  7. School of Cyber Science and Technology, Beihang University, Beijing, Beijing, China

    Dongyu Li

  8. Social Cognition Human-Robot Interaction, Istituto Italiano di Tecnologia, Genoa, Italy

    Jairo Perez-Osorio

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© 2021 This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply

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Wright, B., McCurry, J.M., Lawson, W., Trafton, J.G. (2021). Autonomous Group Detection, Delineation, and Selection for Human-Agent Interaction. In: Li, H., et al. Social Robotics. ICSR 2021. Lecture Notes in Computer Science(), vol 13086. Springer, Cham. https://doi.org/10.1007/978-3-030-90525-5_28

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  • DOI: https://doi.org/10.1007/978-3-030-90525-5_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90524-8

  • Online ISBN: 978-3-030-90525-5

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