Distributed multi-robot formation splitting and merging in dynamic environments

Hai Zhu; Jelle Juhl; Laura Ferranti; Javier Alonso-Mora

doi:10.1109/ICRA.2019.8793765

Distributed multi-robot formation splitting and merging in dynamic environments

Hai Zhu, Jelle Juhl, Laura Ferranti, Javier Alonso-Mora

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

30 Citations (Scopus)

53 Downloads (Pure)

Abstract

This paper presents a distributed method for splitting and merging of multi-robot formations in dynamic environments with static and moving obstacles. Splitting and merging actions rely on distributed consensus and can be performed to avoid obstacles. Our method accounts for the limited communication range and visibility radius of the robots and relies on the communication of obstacle-free convex regions and the computation of an intersection graph. In addition, our method is able to detect and recover from (permanent and temporary) communication and motion faults. Finally, we demonstrate the applicability and scalability of the proposed method in simulations with up to sixteen quadrotors and real-world experiments with a team of four quadrotors.

Original language	English
Title of host publication	Proceedings of the International Conference on Robotics and Automation, ICRA 2019
Place of Publication	Piscataway, NJ, USA
Publisher	IEEE
Pages	9080-9086
ISBN (Electronic)	9781538660263
DOIs	https://doi.org/10.1109/ICRA.2019.8793765
Publication status	Published - 2019
Event	2019 International Conference on Robotics and Automation, ICRA 2019 - Montreal, Canada Duration: 20 May 2019 → 24 May 2019

Publication series

Name	Proceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)	1050-4729

Conference

Conference	2019 International Conference on Robotics and Automation, ICRA 2019
Country/Territory	Canada
City	Montreal
Period	20/05/19 → 24/05/19

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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Distributed_Multi-Robot_Formation_Splitting_and_Merging_in_Dynamic_EnvironmentsFinal published version, 402 KB

Cite this

Zhu, H., Juhl, J., Ferranti, L., & Alonso-Mora, J. (2019). Distributed multi-robot formation splitting and merging in dynamic environments. In Proceedings of the International Conference on Robotics and Automation, ICRA 2019 (pp. 9080-9086). Article 8793765 (Proceedings - IEEE International Conference on Robotics and Automation). IEEE. https://doi.org/10.1109/ICRA.2019.8793765

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title = "Distributed multi-robot formation splitting and merging in dynamic environments",

abstract = "This paper presents a distributed method for splitting and merging of multi-robot formations in dynamic environments with static and moving obstacles. Splitting and merging actions rely on distributed consensus and can be performed to avoid obstacles. Our method accounts for the limited communication range and visibility radius of the robots and relies on the communication of obstacle-free convex regions and the computation of an intersection graph. In addition, our method is able to detect and recover from (permanent and temporary) communication and motion faults. Finally, we demonstrate the applicability and scalability of the proposed method in simulations with up to sixteen quadrotors and real-world experiments with a team of four quadrotors.",

author = "Hai Zhu and Jelle Juhl and Laura Ferranti and Javier Alonso-Mora",

note = "Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 2019 International Conference on Robotics and Automation, ICRA 2019 ; Conference date: 20-05-2019 Through 24-05-2019",

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doi = "10.1109/ICRA.2019.8793765",

language = "English",

series = "Proceedings - IEEE International Conference on Robotics and Automation",

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Zhu, H, Juhl, J, Ferranti, L & Alonso-Mora, J 2019, Distributed multi-robot formation splitting and merging in dynamic environments. in Proceedings of the International Conference on Robotics and Automation, ICRA 2019., 8793765, Proceedings - IEEE International Conference on Robotics and Automation, IEEE, Piscataway, NJ, USA, pp. 9080-9086, 2019 International Conference on Robotics and Automation, ICRA 2019, Montreal, Canada, 20/05/19. https://doi.org/10.1109/ICRA.2019.8793765

Distributed multi-robot formation splitting and merging in dynamic environments. / Zhu, Hai; Juhl, Jelle; Ferranti, Laura et al.
Proceedings of the International Conference on Robotics and Automation, ICRA 2019. Piscataway, NJ, USA: IEEE, 2019. p. 9080-9086 8793765 (Proceedings - IEEE International Conference on Robotics and Automation).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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AB - This paper presents a distributed method for splitting and merging of multi-robot formations in dynamic environments with static and moving obstacles. Splitting and merging actions rely on distributed consensus and can be performed to avoid obstacles. Our method accounts for the limited communication range and visibility radius of the robots and relies on the communication of obstacle-free convex regions and the computation of an intersection graph. In addition, our method is able to detect and recover from (permanent and temporary) communication and motion faults. Finally, we demonstrate the applicability and scalability of the proposed method in simulations with up to sixteen quadrotors and real-world experiments with a team of four quadrotors.

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Distributed multi-robot formation splitting and merging in dynamic environments

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