Distributed multi-robot formation splitting and merging in dynamic environments

Conference Paper (2019)
Author(s)

H. Zhu (TU Delft - Learning & Autonomous Control)

Jelle Juhl (Student TU Delft)

Laura Ferranti (TU Delft - Intelligent Vehicles)

J. Alonso-Mora (TU Delft - Learning & Autonomous Control)

Research Group
Learning & Autonomous Control
Copyright
© 2019 H. Zhu, Jelle Juhl, L. Ferranti, J. Alonso-Mora
DOI related publication
https://doi.org/10.1109/ICRA.2019.8793765
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 H. Zhu, Jelle Juhl, L. Ferranti, J. Alonso-Mora
Research Group
Learning & Autonomous Control
Pages (from-to)
9080-9086
ISBN (electronic)
9781538660263
Reuse Rights

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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.

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