Search and rescue operations in avalanches can greatly benefit from the support of unmanned aerial vehicles, which could safely and autonomously fly above the snow surface to estimate the position of the victim. This work relies upon the Appareil de Recherche de Victimes (ARVA), which consists of a transmitter and a receiver. The transmitter is worn by the victim and produces an electromagnetic field that can be sensed by the receiver, integrated on the drone. A receiver able to sense the complete 3D electromagnetic field has been developed, whose model and properties are presented in this work. The main contribution of this work is the development of a control algorithm able to drive the ARVA-equipped drone as close as possible to the victim location.

Azzollini I.A., Mimmo N., Marconi L. (2020). An extremum seeking approach to search and rescue operations in avalanches using ARVA. RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS : Elsevier B.V. [10.1016/j.ifacol.2020.12.2214].

An extremum seeking approach to search and rescue operations in avalanches using ARVA

Azzollini I. A.
;
Mimmo N.;Marconi L.
2020

Abstract

Search and rescue operations in avalanches can greatly benefit from the support of unmanned aerial vehicles, which could safely and autonomously fly above the snow surface to estimate the position of the victim. This work relies upon the Appareil de Recherche de Victimes (ARVA), which consists of a transmitter and a receiver. The transmitter is worn by the victim and produces an electromagnetic field that can be sensed by the receiver, integrated on the drone. A receiver able to sense the complete 3D electromagnetic field has been developed, whose model and properties are presented in this work. The main contribution of this work is the development of a control algorithm able to drive the ARVA-equipped drone as close as possible to the victim location.
2020
IFAC-PapersOnLine
1627
1632
Azzollini I.A., Mimmo N., Marconi L. (2020). An extremum seeking approach to search and rescue operations in avalanches using ARVA. RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS : Elsevier B.V. [10.1016/j.ifacol.2020.12.2214].
Azzollini I.A.; Mimmo N.; Marconi L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/887925
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