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

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

doi:10.1109/ICUAS.2018.8453430

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

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

Instituto Tecnologico de Estudios Superiores de Monterrey
Concordia University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Scopus citations

Abstract

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.

Original language	English
Title of host publication	2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	702-707
Number of pages	6
ISBN (Print)	9781538613535
DOIs	https://doi.org/10.1109/ICUAS.2018.8453430
State	Published - 31 Aug 2018
Event	2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018 - Dallas, United States Duration: 12 Jun 2018 → 15 Jun 2018

Publication series

Name	2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018

Conference

Conference	2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018
Country/Territory	United States
City	Dallas
Period	12/06/18 → 15/06/18

Access to Document

10.1109/ICUAS.2018.8453430

Cite this

Yungaicela-Naula, N. M., Zhang, Y., Garza-Castanon, L. E., & Minchala, L. I. (2018). UAV-based Air Pollutant Source Localization Using Gradient and Probabilistic Methods. In 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018 (pp. 702-707). Article 8453430 (2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICUAS.2018.8453430

Yungaicela-Naula, Noe M. ; Zhang, Youmin ; Garza-Castanon, Luis E. et al. / UAV-based Air Pollutant Source Localization Using Gradient and Probabilistic Methods. 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 702-707 (2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018).

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title = "UAV-based Air Pollutant Source Localization Using Gradient and Probabilistic Methods",

abstract = "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.",

author = "Yungaicela-Naula, \{Noe M.\} and Youmin Zhang and Garza-Castanon, \{Luis E.\} and Minchala, \{Luis I.\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018 ; Conference date: 12-06-2018 Through 15-06-2018",

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doi = "10.1109/ICUAS.2018.8453430",

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Yungaicela-Naula, NM, Zhang, Y, Garza-Castanon, LE & Minchala, LI 2018, UAV-based Air Pollutant Source Localization Using Gradient and Probabilistic Methods. in 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018., 8453430, 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018, Institute of Electrical and Electronics Engineers Inc., pp. 702-707, 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018, Dallas, United States, 12/06/18. https://doi.org/10.1109/ICUAS.2018.8453430

UAV-based Air Pollutant Source Localization Using Gradient and Probabilistic Methods. / Yungaicela-Naula, Noe M.; Zhang, Youmin; Garza-Castanon, Luis E. et al.
2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 702-707 8453430 (2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Minchala, Luis I.

PY - 2018/8/31

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N2 - 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.

AB - 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.

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DO - 10.1109/ICUAS.2018.8453430

M3 - Contribución a la conferencia

AN - SCOPUS:85053900439

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BT - 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018

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Yungaicela-Naula NM, Zhang Y, Garza-Castanon LE, Minchala LI. UAV-based Air Pollutant Source Localization Using Gradient and Probabilistic Methods. In 2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 702-707. 8453430. (2018 International Conference on Unmanned Aircraft Systems, ICUAS 2018). doi: 10.1109/ICUAS.2018.8453430

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

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