Abstract
This paper reports the use of the first gas dispersion simulator capable of introducing large wind fluctuations into simulations. The proposed simulator enables testing of a modification made to a gas source localization algorithm in a realistic scenario in order to study how the change affects it. Gas source localization in an outdoor environment is a challenging task mainly due to the complexity of the gas spread caused by the unpredictable nature of constantly changing wind. Therefore, a novel use of outdoor wind in developing a gas source localization system by simulation is presented in this paper. To consider the characteristic of sudden but large and unpredictable changes in wind direction, we propose to use recorded outdoor wind to simulate a realistic outdoor gas dispersion which has been done for the first time to the best of our knowledge. With the use of this simulator, we have tested a modification to a mobile robot-based gas source localization algorithm. Multiple simulations of the modified and the original particle filter-based algorithm have been done to study the effect of the tested modification. The results showed that a small difference in the algorithm can greatly impact the results. From this study, we show that the use of simulation consisting of the necessary traits to evaluate outdoor gas source localization, has the potential to accelerate the development of a reliable localization system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Jing, T., Meng, Q.-H., Ishida, H.: Recent progress and trend of robot odor source localization. IEEJ Trans. Electr. Electron. Eng. 16(7), 938–953 (2021). https://doi.org/10.1002/tee.23364
Ishida, H., Nakayama, G., Nakamoto, T., Moriizumi, T.: Controlling a gas/odor plume-tracking robot based on transient responses of gas sensors. IEEE Sens. J. 5(3), 537–545 (2005). https://doi.org/10.1109/JSEN.2004.839597
Vergassola, M., Villermaux, E., Shraiman, B.I.: ‘Infotaxis’ as a strategy for searching without gradients. Nature 445(7126), 406–409 (2007). https://doi.org/10.1038/nature05464
Voges, N., Chaffiol, A., Lucas, P., Martinez, D.: Reactive searching and infotaxis in odor source localization. PLoS Comput. Biol. 10(10), e1003861 (2014). https://doi.org/10.1371/journal.pcbi.1003861
Pang, S., Farrell, J.A.: Chemical plume source localization. IEEE Trans. Syst. Man Cybern. B Cybern. 36(5), 1068–1080 (2006). https://doi.org/10.1109/TSMCB.2006.874689
Ferri, G., et al.: Mapping multiple gas/odor sources in an uncontrolled indoor environment using a Bayesian occupancy grid mapping based method. Rob. Auton. Syst. 59(11), 988–1000 (2011). https://doi.org/10.1016/j.robot.2011.06.007
Li, J.-G., Meng, Q.-H., Wang, Y., Zeng, M.: Odor source localization using a mobile robot in outdoor airflow environments with a particle filter algorithm. Auton. Robot. 30(3), 281–292 (2011). https://doi.org/10.1007/s10514-011-9219-2
Neumann, P.P., Bennetts, V.H., Lilienthal, A.J., Bartholmai, M., Schiller, J.H.: Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms. Adv. Robot. 27(9), 725–738 (2013). https://doi.org/10.1080/01691864.2013.779052
Sakaue, M., Takahashi, Y., Matsukura, H., Ishida, H.: Gas dispersion simulator with strong fluctuations for developing gas source localization systems. In: Proceedings of International Symposium on Olfaction and Electronic Nose. IEEE, New York (2022). https://doi.org/10.1109/ISOEN54820.2022.9789554
Awadalla, M., Lu, T.-F., Tian, Z.F., Dally, B., Liu, Z.: 3D framework combining CFD and MATLAB techniques for plume source localization research. Build. Environ. 70, 10–19 (2013). https://doi.org/10.1016/j.buildenv.2013.07.021
Pashami, S., Asadi, S., Lilienthal, A.: Integration of OpenFOAM flow simulation and filament-based gas propagation models for gas dispersion simulation. In: Proceedings of the Open Source CFD International Conference, vol. 2 (2010)
Monroy, J., Hernandez-Bennetts, V., Fan, H., Lilienthal, A., Gonzalez-Jimenez, J.: GADEN: A 3D gas dispersion simulator for mobile robot olfaction in realistic environments. Sensors 17(7), 1479 (2017). https://doi.org/10.3390/s17071479
Farrell, J.A., Murlis, J., Long, X., Li, W., Cardé, R.T.: Filament-based atmospheric dispersion model to achieve short time-scale structure of odor plumes. Environ. Fluid Mech. 2(1–2), 143–169 (2002). https://doi.org/10.1023/A:1016283702837
Fisher, N.I.: Statistical Analysis of Circular Data. Cambridge University Press, Cambridge (1995)
Sakaue, M., Haratsu, T., Matsukura, H., Neumann, P.P., Ishida, H.: Comparison of two particle-filter-based gas source localization algorithms: use of gas dispersion simulator driven by recorded outdoor wind. Sensors (2022, submitted)
Bilgera, C., Yamamoto, A., Sawano, M., Matsukura, H., Ishida, H.: Application of convolutional long short-term memory neural network to signals collected from a sensor network for autonomous gas source localization in outdoor environments. Sensors 18(12), 4484 (2018). https://doi.org/10.3390/s18124484
Acknowledgments
This work was supported in part by JSPS KAKENHI Grant Numbers 19H02103, 20H02145, and 22H04952.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Haratsu, T., Sakaue, M., Matsukura, H., Neumann, P.P., Ishida, H. (2023). Simulating a Gas Source Localization Algorithm with Gas Dispersion Produced by Recorded Outdoor Wind. In: Tardioli, D., Matellán, V., Heredia, G., Silva, M.F., Marques, L. (eds) ROBOT2022: Fifth Iberian Robotics Conference. ROBOT 2022. Lecture Notes in Networks and Systems, vol 590. Springer, Cham. https://doi.org/10.1007/978-3-031-21062-4_9
Download citation
DOI: https://doi.org/10.1007/978-3-031-21062-4_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-21061-7
Online ISBN: 978-3-031-21062-4
eBook Packages: EngineeringEngineering (R0)