Multi-robot systems are increasingly used in several industry automation and warehouse management applications, mostly with a centralized hub for coordination. Several decentralized infrastructures have been studied for using multi-robot systems in real mission scenarios like search-and-rescue, area coverage and exploration. However, despite designing rigorous methods for using multi-robot systems in a decentralized setting, long-term field deployments still seem unfeasible. The lack of proper infrastructure for tackling fault-detection is one of the great challenges in this regard. We propose FLAM (https://github.com/MISTLab/FLAM), a fault localization and mapping algorithm that detects faults in a robotic system and uses them to build a map of the environmental hazards, effectively providing risk-awareness to the robotic team.


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    Titel :

    FLAM: Fault Localization and Mapping


    Weitere Titelangaben:

    Springer Proceedings in Advanced Robotics


    Beteiligte:
    Bourgeois, Julien (Herausgeber:in) / Paik, Jamie (Herausgeber:in) / Piranda, Benoît (Herausgeber:in) / Werfel, Justin (Herausgeber:in) / Hauert, Sabine (Herausgeber:in) / Pierson, Alyssa (Herausgeber:in) / Hamann, Heiko (Herausgeber:in) / Lam, Tin Lun (Herausgeber:in) / Matsuno, Fumitoshi (Herausgeber:in) / Mehr, Negar (Herausgeber:in)

    Kongress:

    International Symposium on Distributed Autonomous Robotic Systems ; 2022 ; Montbéliard, France November 28, 2022 - November 30, 2022



    Erscheinungsdatum :

    2024-02-01


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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