Unmanned aerial vehicles (UAVs) are nowadays largely employed in civil applications. One of the most promising applications is the environmental monitoring (or risk assessment). We propose a battery-powered eNose board that can be embedded with any type of drone. We evaluated the effectiveness of the sensing method by means of field experiments using the prototype as payload of a hexacopter. The results show that the analysis of the target environmental parameters is not perturbed by the air flow generated by propellers. The system is suitable for any type of mobile carrier (UAVs or wheeled robots), thanks to its lightweight and compact form factor. To further extend the limited flight autonomy of the carrier, we developed an optimal monitoring algorithm for gas leakage localization, a simulating framework to evaluate its performance, and we provide a design space exploration for solar-powered drones.

Autonomous gas detection and mapping with unmanned aerial vehicles / Rossi, Maurizio; Brunelli, Davide. - In: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. - ISSN 0018-9456. - STAMPA. - 65:4(2016), pp. 765-775. [10.1109/TIM.2015.2506319]

Autonomous gas detection and mapping with unmanned aerial vehicles

Rossi, Maurizio;Brunelli, Davide
2016-01-01

Abstract

Unmanned aerial vehicles (UAVs) are nowadays largely employed in civil applications. One of the most promising applications is the environmental monitoring (or risk assessment). We propose a battery-powered eNose board that can be embedded with any type of drone. We evaluated the effectiveness of the sensing method by means of field experiments using the prototype as payload of a hexacopter. The results show that the analysis of the target environmental parameters is not perturbed by the air flow generated by propellers. The system is suitable for any type of mobile carrier (UAVs or wheeled robots), thanks to its lightweight and compact form factor. To further extend the limited flight autonomy of the carrier, we developed an optimal monitoring algorithm for gas leakage localization, a simulating framework to evaluate its performance, and we provide a design space exploration for solar-powered drones.
2016
4
Rossi, Maurizio; Brunelli, Davide
Autonomous gas detection and mapping with unmanned aerial vehicles / Rossi, Maurizio; Brunelli, Davide. - In: IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT. - ISSN 0018-9456. - STAMPA. - 65:4(2016), pp. 765-775. [10.1109/TIM.2015.2506319]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/146416
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