Real-Time FTM-based Victim Positioning System Using Heterogeneous Robots in Remote and Outdoor Scenarios.

dc.centroEscuela de Ingenierías Industrialeses_ES
dc.contributor.authorBravo-Arrabal, Juan
dc.contributor.authorÁlvarez-Merino, Carlos Simón
dc.contributor.authorToscano-Moreno, Manuel
dc.contributor.authorSerón-Barba, Javier
dc.contributor.authorFernández-Lozano, Juan Jesús
dc.contributor.authorGómez-Ruiz, José Antonio
dc.contributor.authorKhatib, Emil Jatib
dc.contributor.authorBarco-Moreno, Raquel
dc.contributor.authorGarcía-Cerezo, Alfonso José
dc.date.accessioned2025-07-04T11:23:38Z
dc.date.available2025-07-04T11:23:38Z
dc.date.issued2025-05-14
dc.departamentoIngeniería de Sistemas y Automáticaes_ES
dc.description.abstractAccurate victim localization in Remote, Outdoor, Unstructured, and Disaster (ROUD) scenarios remains a significant challenge due to limited infrastructure, complex terrains, and time constraints inherent in Search and Rescue (SAR) operations. This article introduces an innovative real-time positioning system that leverages Fine Time Measurement (FTM), a feature of the IEEE 802.11mc amendment, to detect WiFi-enabled devices typically carried by potential victims. The system integrates a Hybrid Wireless Sensor Network (H-WSN) composed of static and mobile anchors mounted on Uncrewed Ground and Aerial Vehicles (UGVs and UAVs), within a Robot Operating System (ROS)-based architecture. A centralized Feedback Information System (FIS) processes real-time RTT data from the field, executes a multilateration algorithm, and provides live geolocation updates to SAR coordinators. The system was validated during a large-scale SAR drill, successfully locating two types of victims—a semi-hidden surface victim and a buried victim—within a 2000m2 area in under 7 minutes, without any filtering or post-processing. The maximum positioning error was 22.87m for the buried victim and 17.14m for the surface one. The complete system, including source code, dataset, and a containerized environment, is openly available to support reproducibility and further research, highlighting the potential of robotic and wireless technologies to enhance disaster response through accurate, real-time localization in complex environments.es_ES
dc.identifier.citationBravo-Arrabal, J., Álvarez-Merino, C. S., Toscano-Moreno, M., Serón-Barba, J., Fernandez-Lozano, J. J., Gómez-Ruiz, J. A., ... & Garcia-Cerezo, A. (2025). Real-Time FTM-based Victim Positioning System Using Heterogeneous Robots in Remote and Outdoor Scenarios. IEEE Access.es_ES
dc.identifier.doi10.1109/ACCESS.2025.3570203
dc.identifier.urihttps://hdl.handle.net/10630/39238
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN//PID2021-122944OB-I00/ES//es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EU/NextGenerationEU///MAORIes_ES
dc.relation.referencesBravo-Arrabal, J., Álvarez-Merino, C. S., Toscano-Moreno, M., Serón-Barba, J., Fernández-Lozano, J. J., Gómez-Ruiz, J. A., Khatib, E. J., & Barco-Moreno, R. (2025). Software for Real-Time FTM-based Victim Positioning Using Heterogeneous Robots in Remote and Outdoor Scenarios. Universidad de Málaga. https://hdl.handle.net/10630/39808
dc.rights.accessRightsopen accesses_ES
dc.subjectRobóticaes_ES
dc.subjectRobots autónomoses_ES
dc.subjectOperaciones de búsqueda y rescatees_ES
dc.subjectRedes de sensores inalámbricases_ES
dc.subjectVehículos teledirigidoses_ES
dc.subjectInformática en la nubees_ES
dc.subject.otherCloud computinges_ES
dc.subject.otherPositioninges_ES
dc.subject.otherROSes_ES
dc.subject.otherSearch and rescuees_ES
dc.subject.otherUncrewed vehicleses_ES
dc.subject.otherWSNes_ES
dc.titleReal-Time FTM-based Victim Positioning System Using Heterogeneous Robots in Remote and Outdoor Scenarios.es_ES
dc.typejournal articlees_ES
dc.type.hasVersionVoRes_ES
dspace.entity.typePublication
relation.isAuthorOfPublicationf7984a4f-fda6-4e40-9e16-4d587f3096bb
relation.isAuthorOfPublicationd12f4139-1d9c-4a85-bf5f-22542c83f2e9
relation.isAuthorOfPublication143621cc-fd1e-44a3-9ec2-c0870aa930e2
relation.isAuthorOfPublicationc933e578-ad80-410f-88c2-f0dbdaa6cf72
relation.isAuthorOfPublication111d26c1-efd3-4b8a-a05b-420a796580e0
relation.isAuthorOfPublication.latestForDiscoveryf7984a4f-fda6-4e40-9e16-4d587f3096bb

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Real-Time_FTM-Based_Victim_Positioning_System_Using_Heterogeneous_Robots_in_Remote_and_Outdoor_Scenarios.pdf
Size:
2.93 MB
Format:
Adobe Portable Document Format
Description:

Collections