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Multi-Robot Systems Research: A Data-Driven Trend Analysis

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Distributed Autonomous Robotic Systems (DARS 2022)

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 28))

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Abstract

This paper provides a data-driven analysis of the trends of research on multi-robot systems (MRS). First, it reports the findings of an exhaustive search of the MRS studies published from 2010 to 2020 in 27 leading robotics journals, including a quantitative analysis of trends. Second, it reports the findings of a survey capturing the views of 68 leading experts in the field of MRSs. Finally, it summarises the findings.

All authors contributed equally to this work.

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Notes

  1. 1.

    The documents of one of the journals (International Journal of Robotics & Automation) could not be accessed in full and were hence excluded.

  2. 2.

    The gender for each prospective participant was estimated. Actual participants could choose to report their gender.

  3. 3.

    See geographic regions on https://unstats.un.org/unsd/methodology/m49/.

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Acknowledgments

This study was conducted as part of the Multi-Robot Systems project (Oct 2019–Dec 2020), which was funded by the Defence Science and Technology Laboratory (contract no DSTL-1000141223). The authors thank the 68 participants of the expert survey, and Alejandro R. Mosteo for feedback on the design of the expert survey.

Author information

Authors and Affiliations

  1. Sheffield Robotics, The University of Sheffield, Sheffield, UK

    João V. Amorim Marques, María-Teresa Lorente & Roderich Groß

  2. INESC Science and Technology, Faculty of Engineering, University of Porto, Sheffield, Portugal

    João V. Amorim Marques

  3. Instituto Tecnológico de Aragón, Zaragoza, Spain

    María-Teresa Lorente

Authors
  1. João V. Amorim Marques
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  2. María-Teresa Lorente
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  3. Roderich Groß
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Corresponding author

Correspondence to Roderich Groß .

Editor information

Editors and Affiliations

  1. University of Franche-Comté, Montbéliard, France

    Julien Bourgeois

  2. École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Jamie Paik

  3. CNRS, University of Franche-Comté, Besancon, France

    Benoît Piranda

  4. Harvard University, Boston, MA, USA

    Justin Werfel

  5. University of Bristol, Bristol, UK

    Sabine Hauert

  6. Boston University, Boston, MA, USA

    Alyssa Pierson

  7. University of Lübeck, Lubeck, Germany

    Heiko Hamann

  8. The Chinese University of Hong Kong, Shenzhen, Shenzhen, China

    Tin Lun Lam

  9. Kyoto University, Kyoto, Japan

    Fumitoshi Matsuno

  10. University of Illinois System, Urbana, IL, USA

    Negar Mehr

  11. University of Franche-Comté, Montbéliard, France

    Abdallah Makhoul

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Marques, J.V.A., Lorente, MT., Groß, R. (2024). Multi-Robot Systems Research: A Data-Driven Trend Analysis. In: Bourgeois, J., et al. Distributed Autonomous Robotic Systems. DARS 2022. Springer Proceedings in Advanced Robotics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-031-51497-5_38

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