Skip to main content
SpringerLink
Log in

A Graph-Based Formation Algorithm for Odor Plume Tracing

  • Conference paper
  • First Online:
Distributed Autonomous Robotic Systems

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 112 ))

Abstract

Odor plume tracing is a challenging robotics application, made difficult by the combination of the patchy characteristics of odor distribution and the slow response of the available sensors. This work proposes a graph-based formation control algorithm to coordinate a group of small robots equipped with odor sensors, with the goal of tracing an odor plume to its source. This approach makes it possible to organize the robots in arbitrary and evolving formation shapes with the aim of improving tracing performance. The algorithm was evaluated in a high-fidelity submicroscopic simulator, using different formations and achieving quick convergence and negligible distance overhead in laminar wind flows.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Cabrita, G., Marques, L., Gazi, V.: Virtual cancelation plume for multiple odor source localization. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5552–5558 (2013). doi:10.1109/IROS.2013.6697161

  2. Cao, M.L., Meng, Q.H., Wang, X.W., Luo, B., Zeng, M., Li, W.: Localization of multiple odor sources via selective olfaction and adapted ant colony optimization algorithm. In: IEEE International Conference on Robotics and Biomimetics, pp. 1222–1227 (2013). doi:10.1109/ROBIO.2013.6739631

  3. de Croon, G., O’Connor, L., Nicol, C., Izzo, D.: Evolutionary robotics approach to odor source localization. Neurocomputing 121, 481–497 (2013). doi:10.1016/j.neucom.2013.05.028

    Article  Google Scholar 

  4. Dhariwal, A., Sukhatme, G., Requicha, A.: Bacterium-inspired robots for environmental monitoring. In: IEEE International Conference on Robotics and Automation, pp. 1436–1443 (2004). doi:10.1109/ROBOT.2004.1308026

  5. Distante, C., Indiveri, G., Reina, G.: An application of mobile robotics for olfactory monitoring of hazardous industrial sites. Ind. Rob. Int. J. 36(1), 51–59 (2009). doi:10.1108/01439910910924675

    Article  Google Scholar 

  6. Falconi, R., Gowal, S., Martinoli, A.: Graph based distributed control of non-holonomic vehicles endowed with local positioning information engaged in escorting missions. In: IEEE International Conference on Robotics and Automation, pp. 3207–3214 (2010). doi:10.1109/ROBOT.2010.5509139

  7. 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). doi:10.1023/A:1016283702837

    Article  Google Scholar 

  8. Genovese, V., Dario, P., Magni, R., Odetti, L.: Self organizing behavior and swarm intelligence in a pack of mobile miniature robots in search of pollutants. IEEE/RSJ Int. Conf. Intell. Rob. Syst. 3, 1575–1582 (1992). doi:10.1109/IROS.1992.594225

    Article  Google Scholar 

  9. Hartman, J.: A possible method for the rapid estimation of flavours in vegetables. Proc. Am. Soc. Hort. Sci. 64, 335–342 (1954)

    Google Scholar 

  10. Hayes, A., Martinoli, A., Goodman, R.: Distributed odor source localization. IEEE Sens. J. 2(3), 260–271 (2002). doi:10.1109/JSEN.2002.800682

    Article  Google Scholar 

  11. Ishida, H., Nakamoto, T., Moriizumi, T., Kikas, T., Janata, J.: Plume-tracking robots: a new application of chemical sensors. Biol. Bull. 200(2), 222–226 (2001)

    Article  Google Scholar 

  12. Jatmiko, W., Sekiyama, K., Fukuda, T.: A PSO-based mobile robot for odor source localization in dynamic advection-diffusion with obstacles environment: theory, simulation and measurement. IEEE Comput. Intell. Mag. 2(2), 37–51 (2007). doi:10.1109/MCI.2007.353419

    Article  Google Scholar 

  13. Khalili, A., Rastegarnia, A., Islam, M.K., Yang, Z.: A bio-inspired cooperative algorithm for distributed source localization with mobile nodes. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3515–3518 (2013). doi:10.1109/EMBC.2013.6610300

  14. Kowadlo, G., Russell, R.A.: Robot odor localization: a taxonomy and survey. Int. J. Robot. Res. 27(8), 869–894 (2008). doi:10.1177/0278364908095118

    Article  Google Scholar 

  15. 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. Rob. 30(3), 281–292 (2011). doi:10.1007/s10514-011-9219-2

    Article  Google Scholar 

  16. Lilienthal, A., Duckett, T.: Experimental analysis of gas-sensitive Braitenberg vehicles. Adv. Robot. 18(8), 817–834 (2004). doi:10.1163/1568553041738103

    Article  Google Scholar 

  17. Lochmatter, T.: Bio-inspired and probabilistic algorithms for distributed odor source localization using mobile robots. Ph.D. thesis 4628, EPFL (2010). doi:10.5075/epfl-thesis-4628

  18. Lochmatter, T., Göl, E., Navarro, I., Martinoli, A.: A plume tracking algorithm based on crosswind formations. In: International Symposium on Distributed Autonomous Robotic Systems. Springer Tracts in Advanced Robotics (2013), vol. 83, pp. 91–102 (2010). doi:10.1007/978-3-642-32723-0_7

    Google Scholar 

  19. Marjovi, A., Marques, L.: Optimal swarm formation for odor plume finding. IEEE Trans. Cybern. 99 (2014). doi:10.1109/TCYB.2014.2306291

    Google Scholar 

  20. Marques, L., Nunes, U., de Almeida, A.T.: Olfaction-based mobile robot navigation. Thin Solid Films 418(1), 51–58 (2002). doi:10.1016/S0040-6090(02)00593-X

    Article  Google Scholar 

  21. Marques, L., Nunes, U., Almeida, A.T.: Particle swarm-based olfactory guided search. Auton. Rob. 20(3), 277–287 (2006). doi:10.1007/s10514-006-7567-0

    Article  Google Scholar 

  22. Mesbahi, M., Egerstedt, M.: Graph Theoretic Methods in Multiagent Networks. Princeton University Press, Princeton (2010)

    Google Scholar 

  23. Michel, O.: Webots: professional mobile robot simulation. Int. J. Adv. Rob. Syst. 1(1), 39–42 (2004). doi:10.5772/5618

    Google Scholar 

  24. Moncrieff, R.W.: An instrument for measuring and classifying odors. J. Appl. Physiol. 16(4), 742–749 (1961)

    Google Scholar 

  25. Pugh, J., Raemy, X., Favre, C., Falconi, R., Martinoli, A.: A Fast onboard relative positioning module for multirobot systems. IEEE/ASME Trans. Mechatron. 14(2), 151–162 (2009). doi:10.1109/TMECH.2008.2011810

    Article  Google Scholar 

  26. Roberts, P.J.W., Webster, D.R.: Turbulent Diffusion. ASCE Press, Reston, Virginia (2002)

    Google Scholar 

  27. Rozas, R., Morales, J., Vega, D.: Artificial smell detection for robotic navigation. In: International Conference on Advanced Robotics, pp. 1730–1733 (1991). doi:10.1109/ICAR.1991.240354

  28. Vergassola, M., Villermaux, E., Shraiman, B.I.: ‘Infotaxis’ as a strategy for searching without gradients. Nature 445(7126), 406–409 (2007). doi:10.1038/nature05464

    Article  Google Scholar 

Download references

Acknowledgments

This work was partially funded by project PEst-OE/EEI/LA0009/2013 and grant SFRH/BD/51073/2010 from Fundação para a Ciência e Tecnologia. We sincerely thank Ali Marjovi at DISAL for the detailed and constructive comments.

Author information

Authors and Affiliations

  1. Distributed Intelligent Systems and Algorithms Laboratory, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Jorge M. Soares & Alcherio Martinoli

  2. Institute for Systems and Robotics, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal

    Jorge M. Soares & António M. Pascoal

  3. Department of Electrical and Computer Engineering, Faculty of Engineering, University of Porto, Porto, Portugal

    A. Pedro Aguiar

  4. National Institute of Oceanography, Dona Paula, Goa, India

    António M. Pascoal

Authors
  1. Jorge M. Soares
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Pedro Aguiar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. António M. Pascoal
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alcherio Martinoli
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jorge M. Soares .

Editor information

Editors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Nak-Young Chong

  2. Electronics and Telecommunications Research Institute, Daejeon, Korea (Republic of)

    Young-Jo Cho

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Japan

About this paper

Cite this paper

Soares, J.M., Aguiar, A.P., Pascoal, A.M., Martinoli, A. (2016). A Graph-Based Formation Algorithm for Odor Plume Tracing. In: Chong, NY., Cho, YJ. (eds) Distributed Autonomous Robotic Systems. Springer Tracts in Advanced Robotics, vol 112 . Springer, Tokyo. https://doi.org/10.1007/978-4-431-55879-8_18

Download citation

  • DOI: https://doi.org/10.1007/978-4-431-55879-8_18

  • Published:

  • Publisher Name: Springer, Tokyo

  • Print ISBN: 978-4-431-55877-4

  • Online ISBN: 978-4-431-55879-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation