UAV-based Air Pollutant Source Localization Using Gradient and Probabilistic Methods

Noe M. Yungaicela-Naula, Youmin Zhang, Luis E. Garza-Castanon, Luis I. Minchala

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

10 Citas (Scopus)

Resumen

This work proposes an algorithm for air pollutant source localization using an Unmanned Aerial Vehicle (UAV). The algorithm combines a gradient-based search with a probabilistic method to localize the pollutant source. The design of the gradient-based search component is based on the simulated annealing metaheuristic and allows to trace the plume of pollutant. The probabilistic component contributes to generate a heuristic position of the source location, which is used by the gradient-based metaheuristic to navigate towards the source position, reducing the searching region at each sampling time. The proposed algorithm was tested in a simulated polluted environment. The results showed high effectiveness and robustness of the proposed strategy.

Idioma originalInglés
Título de la publicación alojada2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas702-707
Número de páginas6
ISBN (versión impresa)9781538613535
DOI
EstadoPublicada - 31 ago. 2018
Evento2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018 - Dallas, Estados Unidos
Duración: 12 jun. 201815 jun. 2018

Serie de la publicación

Nombre2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018

Conferencia

Conferencia2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018
País/TerritorioEstados Unidos
CiudadDallas
Período12/06/1815/06/18

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