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Toward a Heterogeneous Multi-robot Framework for Priority-Based Sanitization of Railway Stations

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AIxIA 2022 – Advances in Artificial Intelligence (AIxIA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13796))

Abstract

We present a new framework for the prioritized multi-robot sanitization of railway stations based on Deep Reinforcement Learning. The proposed framework allows us to define teams of robots having different sanitizing strategies/capabilities, e.g., faster robots rapidly sanitizing small areas in cooperation with slower but long-range ones. Here, robot-specific policies are defined in order to accommodate the different capabilities of the single agents, while two global metrics are defined to assess the performance of the overall team. This capability of managing heterogeneous teams is an important requirement for the infrastructure manager Rete Ferroviaria Italiana S.p.A., which plans to verify to what extent different technologies or different strategies can be combined to reduce costs or increase cleaning efficiency. We tested our framework considering real data collected by the WiFi network of the main Italian railway station, Roma Termini, comparing its results with a similar Deep Reinforcement Learning system where homogeneous robots are employed.

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Author information

Authors and Affiliations

  1. Università degli studi di Napoli “Federico II”, via Claudio 21, 80125, Naples, Italy

    Riccardo Caccavale, Alberto Finzi, Vincenzo Lippiello & Fabrizio Tavano

  2. Rete Ferroviaria Italiana, Piazza della Croce Rossa 1, 00161, Rome, Italy

    Mirko Ermini, Eugenio Fedeli & Fabrizio Tavano

Authors
  1. Riccardo Caccavale
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  2. Mirko Ermini
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  3. Eugenio Fedeli
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  4. Alberto Finzi
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  5. Vincenzo Lippiello
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  6. Fabrizio Tavano
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Corresponding author

Correspondence to Fabrizio Tavano .

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Editors and Affiliations

  1. University of Udine, Udine, Italy

    Agostino Dovier

  2. University of Udine, Udine, Italy

    Angelo Montanari

  3. National Research Council (CNR-ISTC), Rome, Italy

    Andrea Orlandini

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Caccavale, R., Ermini, M., Fedeli, E., Finzi, A., Lippiello, V., Tavano, F. (2023). Toward a Heterogeneous Multi-robot Framework for Priority-Based Sanitization of Railway Stations. In: Dovier, A., Montanari, A., Orlandini, A. (eds) AIxIA 2022 – Advances in Artificial Intelligence. AIxIA 2022. Lecture Notes in Computer Science(), vol 13796. Springer, Cham. https://doi.org/10.1007/978-3-031-27181-6_27

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  • DOI: https://doi.org/10.1007/978-3-031-27181-6_27

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