2026-05-28T20:42:04Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/392382026-02-03T11:30:38Zcom_10630_2254col_10630_37953

Real-Time FTM-based Victim Positioning System Using Heterogeneous Robots in Remote and Outdoor Scenarios. Bravo-Arrabal, Juan Álvarez-Merino, Carlos Simón Toscano-Moreno, Manuel Serón-Barba, Javier Fernández-Lozano, Juan Jesús Gómez-Ruiz, José Antonio Khatib, Emil Jatib Barco-Moreno, Raquel García-Cerezo, Alfonso José Robótica Robots autónomos Operaciones de búsqueda y rescate Redes de sensores inalámbricas Vehículos teledirigidos Informática en la nube Accurate 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. 2025-07-04T11:23:38Z 2025-07-04T11:23:38Z 2025-07-04T11:23:38Z 2025-05-14 journal article Bravo-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. https://hdl.handle.net/10630/39238 10.1109/ACCESS.2025.3570203 eng Bravo-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 info:eu-repo/grantAgreement/MICINN//PID2021-122944OB-I00/ES// info:eu-repo/grantAgreement/EU/NextGenerationEU///MAORI open access IEEE