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Plume Tracking by a Self-stabilized Group of Micro Aerial Vehicles

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8906))

Abstract

A cooperative odor plume tracking approach designed for use with groups of micro-scale, autonomous helicopters in GNSS-denied environment is proposed in this paper. The designed method is based on a particle swarm optimization enhanced for efficient and fast cooperative searching for gas sources. The possibility of MAVs deployment in GNSS-denied environment is enabled by employed visual relative localization using onboard monocular cameras and identification patterns. In addition to constraints given by the relative localization (necessity of direct visibility and limited range of the system), MAV motion constraints and non-colliding multi-robot coordination are satisfied in the method. The developed method has been verified using a numerical model of smoke plume in various simulations and real experiments with a fleet of MAVs.

This work was supported by GAČR under postdoc grant of Martin Saska no. P103-12/P756.

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References

  1. Bartholmai, M., Neumann, P.: Micro-drone for gas measurement in hazardous scenarios via remote sensing. In: WSEAS International Conference on Remote Sensing (2010)

    Google Scholar 

  2. Caltabiano, D., Muscato, G., Orlando, A., Federico, C., Giudice, G., Guerrieri, S.: Architecture of a uav for volcanic gas sampling. In: 10th IEEE Conference on Emerging Technologies and Factory Automation (2005)

    Google Scholar 

  3. Ishida, H., Nakayama, G., Nakamoto, T., Moriizumi, T.: Controlling a gas/odor plume-tracking robot based on transient responses of gas sensors. In: Proceedings of IEEE Sensors (2002)

    Google Scholar 

  4. Ishida, H., Yoshikawa, K., Moriizumi, T.: Three-dimensional gas-plume tracking using gas sensors and ultrasonic anemometer. In: Proceedings of IEEE Sensors (2004)

    Google Scholar 

  5. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings IEEE International Conference on Neural Networks (1995)

    Google Scholar 

  6. Lee, T., Leoky, M., McClamroch, N.: Geometric tracking control of a quadrotor uav on se(3). In: 49th IEEE Conference on Decision and Control (CDC) (2010)

    Google Scholar 

  7. Li, J., Meng, Q., Wang, Y., Zeng, M.: Odor source localization using a mobile robot in outdoor air flow environments with a particle filter algorithm. Autonomous Robots 30(3), 281–292 (2011)

    Article  Google Scholar 

  8. Marjovi, A., Marques, L.: Swarm robotic plume tracking for intermittent and time-variant odor dispersion. In: European Conference on Mobile Robots (ECMR) (2013)

    Google Scholar 

  9. Saska, M., Chudoba, J., Preucil, L., Thomas, J., Loianno, G., Tresnak, A., Vonasek, V., Kumar, V.: Autonomous deployment of swarms of micro-aerial vehicles in cooperative surveillance. In: ICUAS (2014)

    Google Scholar 

  10. Saska, M., Kasl, Z., Preucil, L.: Motion planning and control of formations of micro aerial vehicles. In: IFAC World Congress (2014)

    Google Scholar 

  11. Scheutz, M., Schermerhorn, P., Bauer, P.: The utility of heterogeneous swarms of simple uavs with limited sensory capacity in detection and tracking tasks. In: Proceedings 2005 IEEE Swarm Intelligence Symposium (2005)

    Google Scholar 

  12. Waphare, S., Gharpure, D., Shaligram, A., Botre, B.: Implementation of 3-nose strategy in odor plume-tracking algorithm. In: International Conference on Signal Acquisition and Processing, ICSAP 2010 (2010)

    Google Scholar 

  13. Yuli, Z., Xiaoping, M., Yanzi, M.: Localization of multiple odor sources using modified glowworm swarm optimization with collective robots. In: 30th Chinese Control Conference (CCC) (2011)

    Google Scholar 

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© 2014 Springer International Publishing Switzerland

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Saska, M., Langr, J., Přeučil, L. (2014). Plume Tracking by a Self-stabilized Group of Micro Aerial Vehicles. In: Hodicky, J. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2014. Lecture Notes in Computer Science, vol 8906. Springer, Cham. https://doi.org/10.1007/978-3-319-13823-7_5

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  • DOI: https://doi.org/10.1007/978-3-319-13823-7_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13822-0

  • Online ISBN: 978-3-319-13823-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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