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A distributed architecture for supervision of autonomous multi-robot missions

Application to air-sea scenarios

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Abstract

Realizing long-term autonomous missions involving teams of heterogeneous robots is a challenge. It requires mechanisms to make robots react to disturbances or failures that will arise during the mission, while trying to successfully achieve the mission in cooperation. This paper presents HiDDeN, a distributed deliberative architecture that manages the execution of a hierarchical plan. This plan has initially been computed offline, ensuring some military operational constraints of the mission. Each robot’s supervisor then executes its own part of the plan, and reacts to failures using a hierarchical repair approach. This hierarchical repair has been designed with the sake of ensuring operational constraints, while reducing the need of communication between robots, as communication may be intermittent or even nonexistent when the robots operate in completely separate environments. HiDDeN’s robustness and scalability is evaluated with simulations. Experiments with an autonomous helicopter and an autonomous underwater vehicle have been realized and are presented as the defining point of our contribution.

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Acknowledgments

The authors thanks the French Defense procurement agency DGA for the funding of the ACTION project and for their strong involvement in the air-sea scenarios with developments and implementation on Daurade AUV and Spartan USV and for provision of the test site.

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Authors and Affiliations

  1. ONERA – The French Aerospace Lab, 2, av. Edouard Belin, 31000, Toulouse, France

    Charles Lesire, Guillaume Infantes & Magali Barbier

  2. Institut Supérieur de l’Aéronautique et de l’Espace (ISAE), 10, av. Edouard Belin, 31055, Toulouse, France

    Thibault Gateau

Authors
  1. Charles Lesire
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  2. Guillaume Infantes
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  3. Thibault Gateau
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  4. Magali Barbier
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Correspondence to Charles Lesire.

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Lesire, C., Infantes, G., Gateau, T. et al. A distributed architecture for supervision of autonomous multi-robot missions. Auton Robot 40, 1343–1362 (2016). https://doi.org/10.1007/s10514-016-9603-z

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