Essec\Faculty\Model\Contribution {#2233
  #_index: "academ_contributions"
  #_id: "15607"
  #_source: array:26 [
    "id" => "15607"
    "slug" => "15607-formation-analysis-for-a-fleet-of-drones-a-mathematical-framework"
    "yearMonth" => "2025-04"
    "year" => "2025"
    "title" => "Formation Analysis for a Fleet of Drones: A Mathematical Framework"
    "description" => "TRAVERSI, E., BARCIS, M., BELLONE, L., BARCIS, A., AHMIM-BONALDI, D., FERRANTE, E. et NATALIZIO, E. (2025). Formation Analysis for a Fleet of Drones: A Mathematical Framework. Dans: <i>Proceedings of the 17th International Conference on Agents and Artificial Intelligence</i>. Porto:  SCITEPRESS - Science and Technology Publications, pp. 471-480."
    "authors" => array:7 [
      0 => array:3 [
        "name" => "TRAVERSI Emiliano"
        "bid" => "B00820417"
        "slug" => "traversi-emiliano"
      ]
      1 => array:1 [
        "name" => "Barcis Michal"
      ]
      2 => array:1 [
        "name" => "Bellone Lorenzo"
      ]
      3 => array:1 [
        "name" => "Barcis Agata"
      ]
      4 => array:1 [
        "name" => "Ahmim-Bonaldi Dina"
      ]
      5 => array:1 [
        "name" => "Ferrante Eliseo"
      ]
      6 => array:1 [
        "name" => "Natalizio Enrico"
      ]
    ]
    "ouvrage" => "Proceedings of the 17th International Conference on Agents and Artificial Intelligence"
    "keywords" => array:3 [
      0 => "Robot and Multi-Robot Systems"
      1 => "Task Planning and Execution"
      2 => "Formation Study"
    ]
    "updatedAt" => "2025-04-23 09:52:32"
    "publicationUrl" => "https://doi.org/10.5220/0013189400003890"
    "publicationInfo" => array:3 [
      "pages" => "471-480"
      "volume" => "1"
      "number" => ""
    ]
    "type" => array:2 [
      "fr" => "Actes d'une conférence"
      "en" => "Conference Proceedings"
    ]
    "support_type" => array:2 [
      "fr" => "Editeur"
      "en" => "Publisher"
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "We consider a dynamic coverage scenario, where a group of agents (e.g., Unmanned Aerial Vehicles (UAVs)) is exploring an environment in search of a moving target (e.g., survivors on a lifeboat). We assume UAVs are capable to achieve, maintain, and move in formation (e.g., to maintain connectivity). This paper addresses the question “Which formation maximizes the chance of finding the target?”. We propose a mathematical framework to answer this question. The proposed framework is generic and can be easily applied to various formations and missions. We show how the framework can identify which formation will result in better performance in the type of missions we consider. We analyze how different factors, namely the target speed relative to the group, affect the performance of the formations. We validate the framework against simulations of the considered scenarios. The supplementary video material including the real-world implementation is available at https://youtu.be/ mYmTnAJi-I?si"
      "en" => "We consider a dynamic coverage scenario, where a group of agents (e.g., Unmanned Aerial Vehicles (UAVs)) is exploring an environment in search of a moving target (e.g., survivors on a lifeboat). We assume UAVs are capable to achieve, maintain, and move in formation (e.g., to maintain connectivity). This paper addresses the question “Which formation maximizes the chance of finding the target?”. We propose a mathematical framework to answer this question. The proposed framework is generic and can be easily applied to various formations and missions. We show how the framework can identify which formation will result in better performance in the type of missions we consider. We analyze how different factors, namely the target speed relative to the group, affect the performance of the formations. We validate the framework against simulations of the considered scenarios. The supplementary video material including the real-world implementation is available at https://youtu.be/ mYmTnAJi-I?si"
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2025-12-06T08:21:43.000Z"
    "docTitle" => "Formation Analysis for a Fleet of Drones: A Mathematical Framework"
    "docSurtitle" => "Actes d'une conférence"
    "authorNames" => "<a href="/cv/traversi-emiliano">TRAVERSI Emiliano</a>, Barcis Michal, Bellone Lorenzo, Barcis Agata, Ahmim-Bonaldi Dina, Ferrante Eliseo, Natalizio Enrico"
    "docDescription" => "<span class="document-property-authors">TRAVERSI Emiliano, Barcis Michal, Bellone Lorenzo, Barcis Agata, Ahmim-Bonaldi Dina, Ferrante Eliseo, Natalizio Enrico</span><br><span class="document-property-authors_fields">Systèmes d'Information, Data Analytics et Opérations</span> | <span class="document-property-year">2025</span>"
    "keywordList" => "<a href="#">Robot and Multi-Robot Systems</a>, <a href="#">Task Planning and Execution</a>, <a href="#">Formation Study</a>"
    "docPreview" => "<b>Formation Analysis for a Fleet of Drones: A Mathematical Framework</b><br><span>2025-04 | Actes d'une conférence </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://doi.org/10.5220/0013189400003890" target="_blank">Formation Analysis for a Fleet of Drones: A Mathematical Framework</a>"
  ]
  +lang: "fr"
  +"_score": 8.687645
  +"_ignored": array:3 [
    0 => "abstract.en.keyword"
    1 => "abstract.fr.keyword"
    2 => "description.keyword"
  ]
  +"parent": null
}