TY - GEN
T1 - Gas Source Localization Based on Binary Sensing with a UAV
AU - Wiedemann, Thomas
AU - Schaab, Marius
AU - Gomez, Juan Marchal
AU - Shutin, Dmitriy
AU - Scheibe, Monika
AU - Lilienthal, Achim J.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Precise gas concentration measurements are often difficult, especially by in-situ sensors mounted on an Unmanned Aerial Vehicle (UAV). Simple gas detection, on the other hand, is more robust and reliable, yet brings significantly less information for gas source localization. In this paper, we compensate for the lack of information by a physical model of gas propagation based on the advection-diffusion Partial Differential Equation (PDE). By linking binary gas detection measurements to computed gas concentration using the physical model and an appropriately designed likelihood function, it becomes possible to identify the most likely gas source distribution. The approach was validated in two experiments with ethanol and smoke as 'toy' gasses. It is shown that the method is able to successfully localize the source locations in experiments based on gas detection measurements taken by a UAV.
AB - Precise gas concentration measurements are often difficult, especially by in-situ sensors mounted on an Unmanned Aerial Vehicle (UAV). Simple gas detection, on the other hand, is more robust and reliable, yet brings significantly less information for gas source localization. In this paper, we compensate for the lack of information by a physical model of gas propagation based on the advection-diffusion Partial Differential Equation (PDE). By linking binary gas detection measurements to computed gas concentration using the physical model and an appropriately designed likelihood function, it becomes possible to identify the most likely gas source distribution. The approach was validated in two experiments with ethanol and smoke as 'toy' gasses. It is shown that the method is able to successfully localize the source locations in experiments based on gas detection measurements taken by a UAV.
KW - airborne sensing
KW - gas dispersion model
KW - gas source localization
KW - unmanned aerial vehicle
UR - https://www.scopus.com/pages/publications/85133168217
U2 - 10.1109/ISOEN54820.2022.9789553
DO - 10.1109/ISOEN54820.2022.9789553
M3 - Conference contribution
AN - SCOPUS:85133168217
T3 - International Symposium on Olfaction and Electronic Nose, ISOEN 2022 - Proceedings
BT - International Symposium on Olfaction and Electronic Nose, ISOEN 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Symposium on Olfaction and Electronic Nose, ISOEN 2022
Y2 - 29 May 2022 through 1 June 2022
ER -