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Intelligent Drone Swarms to Search for Victims in Post-Disaster Areas.
Haddad, Matheus Nohra; Santos, Andréa Cynthia; Duhamel, Christophe; Coco, Amadeu Almeida.
Afiliación
  • Haddad MN; LITIS, ISEL, Université Le Havre Normandie, 25 Rue Philippe Lebon, 76600 Le Havre, France.
  • Santos AC; CRP-IEP, Universidade Federal de Viçosa, Km 7, MG-230, Rodoviário, Rio Paranaíba 38810-000, Brazil.
  • Duhamel C; LITIS, ISEL, Université Le Havre Normandie, 25 Rue Philippe Lebon, 76600 Le Havre, France.
  • Coco AA; LITIS, ISEL, Université Le Havre Normandie, 25 Rue Philippe Lebon, 76600 Le Havre, France.
Sensors (Basel) ; 23(23)2023 Nov 30.
Article en En | MEDLINE | ID: mdl-38067913
This study presents the Drone Swarms Routing Problem (DSRP), which consists of identifying the maximum number of victims in post-disaster areas. The post-disaster area is modeled in a complete graph, where each search location is represented by a vertex, and the edges are the shortest paths between destinations, with an associated weight, corresponding to the battery consumption to fly to a location. In addition, in the DSRP addressed here, a set of drones are deployed in a cooperative drone swarms approach to boost the search. In this context, a V-shaped formation is applied with leader replacements, which allows energy saving. We propose a computation model for the DSRP that considers each drone as an agent that selects the next search location to visit through a simple and efficient method, the Drone Swarm Heuristic. In order to evaluate the proposed model, scenarios based on the Beirut port explosion in 2020 are used. Numerical experiments are presented in the offline and online versions of the proposed method. The results from such scenarios showed the efficiency of the proposed approach, attesting not only the coverage capacity of the computational model but also the advantage of adopting the V-shaped formation flight with leader replacements.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Francia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Francia