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Título:
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Chemical source localization fusing concentration information in the presence of chemical background noise
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Autor/a:
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Pomareda, Víctor; Magrans, Rudys; Jiménez Soto, Juan M.; Martínez Lacasa, Daniel; Tresánchez Ribes, Marcel; Burgués, Javier; Palacín Roca, Jordi; Marco, Santiago
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Notas:
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We present the estimation of a likelihood map for the location of the source of a chemical
plume dispersed under atmospheric turbulence under uniform wind conditions. The main
contribution of this work is to extend previous proposals based on Bayesian inference with binary
detections to the use of concentration information while at the same time being robust against the
presence of background chemical noise. For that, the algorithm builds a background model with
robust statistics measurements to assess the posterior probability that a given chemical concentration
reading comes from the background or from a source emitting at a distance with a specific release rate.
In addition, our algorithm allows multiple mobile gas sensors to be used. Ten realistic simulations
and ten real data experiments are used for evaluation purposes. For the simulations, we have
supposed that sensors are mounted on cars which do not have among its main tasks navigating
toward the source. To collect the real dataset, a special arena with induced wind is built, and an
autonomous vehicle equipped with several sensors, including a photo ionization detector (PID) for
sensing chemical concentration, is used. Simulation results show that our algorithm, provides a better
estimation of the source location even for a low background level that benefits the performance of
binary version. The improvement is clear for the synthetic data while for real data the estimation
is only slightly better, probably because our exploration arena is not able to provide uniform wind
conditions. Finally, an estimation of the computational cost of the algorithmic proposal is presented.
The research leading to these results has received funding from the European Community’s
Seventh Framework Programme (FP7/2007-2013) under Grant Agreement No. 217925: LOTUS: Localization of
Threat Substances in an Urban Society. This work was partially funded by the Spanish MINECO program, under
grants TEC2011-26143 (SMART-IMS), TEC2014-59229-R (SIGVOL), and BES-2015-071698 (SEVERO-OCHOA).
The Signal and Information Processing for Sensor Systems group is a consolidated Grup de Recerca de la
Generalitat de Catalunya and has support from the Departament d’Universitats, Recerca i Societat de la Informació
de la Generalitat de Catalunya (expedient 2014-SGR-1445). This work has received support from the Comissionat
per a Universitats i Recerca del DIUE de la Generalitat de Catalunya and the European Social Fund (ESF).
Additional financial support has been provided by the Institut de Bioenginyeria de Catalunya (IBEC). IBEC is
a member of the CERCA Programme/Generalitat de Catalunya. |
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Materia(s):
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-Machine olfaction
-Odor robots
-Chemical sensors
-Bayesian inference |
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Derechos:
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cc-by (c) Pomareda et al., 2017
http://creativecommons.org/licenses/by/4.0/
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Tipo de documento:
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article
publishedVersion |
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Editor:
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MDPI
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Compartir:
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