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Hybrid Flock - Formation Control Algorithms

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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

Two prominent categories of algorithms for achieving coordinated multi-robot displacement are flocking and navigation in formation. Both categories have their own body of literature and characteristics, including their respective advantages and disadvantages. Although typically they are treated separately, we believe that a combination of flock and formation control represents a promising algorithmic solution. Such an algorithm could take advantage of a combination of characteristics of both categories that are best suited for a given situation. Therefore, in this work, we propose two distributed algorithms capable of gradually and reversibly shifting between flocking and formation behaviors using a single parameter \(\mathcal {W}\). We evaluate them using both simulated and real robots with and without the presence of obstacles. We find that both algorithms successfully trade off flock density for formation error. Furthermore, leveraging a narrow passage experiment as an application case study, we demonstrate that an adaptive shift between flock and formation behavior, adopting a simple method to define \(\mathcal {W}\) in real-time using exclusively on-board resources, results in a statistically relevant reduction of traversing time in comparison to a non-adaptive formation control algorithm.

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Acknowledgements

We would like to thank Masaki Haruna, Masahiko Kurishige and Tomoki Emmei of the Advanced Technology R &D Center, Mitsubishi Electric Corporation, Amagasaki City, Japan for the fruitful technical discussions all along this work. This work is financially supported by Mitsubishi Electric Corporation, Japan.

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Authors and Affiliations

  1. Distributed Intelligent Systems and Algorithms Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Cyrill Baumann, Jonas Perolini, Emna Tourki & Alcherio Martinoli

Authors
  1. Cyrill Baumann
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  2. Jonas Perolini
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  3. Emna Tourki
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  4. Alcherio Martinoli
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Corresponding author

Correspondence to Cyrill Baumann .

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

Appendix

Appendix

A video of the experiments performed for this contribution can be found on our research web page: www.epfl.ch/labs/disal/research/mrsmodelingcontrol.

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Baumann, C., Perolini, J., Tourki, E., Martinoli, A. (2024). Hybrid Flock - Formation Control Algorithms. 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_37

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