Skip to main content

Embodiment Sensing for Self-generated Zigzag Turning Algorithm Using Vision-Based Plume Diffusion

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8810))

Abstract

Biomimetic Chemical Plume Tracing (CPT) problem is complex because it couples nonlinearity of biological systems with uncertainty of time-varying plume diffusion. A vision-based simulator is proposed to decouple these difficulties to facilitate multiple runs under controlled environment. This enables identification of efficient biological CPT algorithm. The simulator is used to simulate Embodiment Sensing (ES), i.e. sensing using physical attributes of animals. Wings and antennae of silk moth are used for ES, and evaluated for CPT using vision-based simulator. Results suggest (1) vision-based plume field mimics actual plume diffusion in terms intermittency, and (2) similar performance as that for surge-cast algorithm. The contribution is two-fold, (1) vision-based plume diffusion simulator decouples uncertainty of plume diffusion from nonlinearity of biological system to facilitate biomimetic CPT study, and (2) feasibility of using physical attributes of silk moth to achieve good CPT performance.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Settles, G.S.: Sniffers: Fluid dynamic sampling for olfactory trace detection in nature and homeland security. J. Fluids Eng. 127, 189–218 (2005)

    Article  Google Scholar 

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

    Article  Google Scholar 

  3. Trincavelli, M., Coradeschi, S., Loutfi, A.: Classification of odors with mobile robots based on transient response. In: IEEE/RSJ Int. Conf. Intelligent Robots and Systems, pp. 4110–4115. IEEE Press, New York (2008)

    Google Scholar 

  4. Liu, Z.Z.: Odor source localization using multiple plume-tracking mobile robots. Ph.D dissertation, Dept. Mech. Eng., Univ. Adelaide, Australia (2010)

    Google Scholar 

  5. Zarzhitsky, D., Spears, D., Thayer, D., Spears, W.: Agent-based chemical plume tracing using fluid dynamics. In: Hinchey, M.G., Rash, J.L., Truszkowski, W.F., Rouff, C.A. (eds.) FAABS 2004. LNCS (LNAI), vol. 3228, pp. 146–160. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  6. Meng, Q.H., Yang, W.X., Wang, Y., Li, F., Zeng, M.: Adapting an ant colony metaphor for multi-robot chemical plume tracing. Sensors 12, 4737–4763 (2012)

    Article  Google Scholar 

  7. Ando, N., Emoto, S., Kanzaki, R.: Odor-tracking capability of a silkmoth driving a mobile robot with turning bias and time delay. Bioinspir. Biomim. 8, 1–14 (2013)

    Article  Google Scholar 

  8. Kanzaki, R., Sugi, N., Shibuya, T.: Self-generated zigzag turning of Bombyx Mori males during pheromone-mediated upwind walking. Zool. Sci. 9, 515–527 (1992)

    Google Scholar 

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

    Article  Google Scholar 

  10. Russell, R.A., Bab-Hadiashar, A., Shepherd, R.L., Wallace, G.G.: A comparison of reactive robot chemotaxis algorithms. Robotics and Autonomous Systems 45, 83–97 (2003)

    Article  Google Scholar 

  11. Lochmatter, T., Martinoli, A.: Tracking odor plumes in a laminar wind field with bio-inspired algorithms. In: Khatib, O., Kumar, V., Pappas, G.J. (eds.) Experimental Robotics. STAR, vol. 54, pp. 473–482. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  12. Chew, J.Y., Kurabayashi, D.: Quantitative analysis of the silk moth’s chemical plume tracing locomotion using a hierarchical classification method. J. Bionic Eng. 2, 268–281 (2014)

    Article  Google Scholar 

  13. Li, W., Farrell, J.A., Pang, S., Arrieta, R.M.: Moth-inspired chemical plume tracing on an autonomous underwater vehicle. IEEE Transactions on Robotics 22, 292–307 (2006)

    Article  Google Scholar 

  14. Pang, S., Farrell, J.A.: Chemical Plume Source Localization. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 36, 1068–1080 (2006)

    Article  Google Scholar 

  15. Li, J.G., Yang, J., Cui, S.G., Geng, L.H.: Speed limitation of a mobile robot and methodology of tracing odor plume in airflow environments. Procedia Eng. 15, 1041–1045 (2011)

    Article  Google Scholar 

  16. Harvey, D.J., Lu, T.F., Keller, M.A.: Comparing insect-inspired chemical plume tracking algorithms using a mobile robot. IEEE Trans. Robot. 24, 307–317 (2008)

    Article  Google Scholar 

  17. Serra, J.: Image analysis and mathematical morphology. Academic Press, USA (1983)

    Google Scholar 

  18. Loudon, C., Koehl, M.A.R.: Sniffing by a silkworm moth: wing fanning enhances air penetration through and pheromone interception by antennae. Journal of Experimental Biology 203, 2977–2990 (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Chew, J.Y., Yoshihara, T., Kurabayashi, D. (2014). Embodiment Sensing for Self-generated Zigzag Turning Algorithm Using Vision-Based Plume Diffusion. In: Brugali, D., Broenink, J.F., Kroeger, T., MacDonald, B.A. (eds) Simulation, Modeling, and Programming for Autonomous Robots. SIMPAR 2014. Lecture Notes in Computer Science(), vol 8810. Springer, Cham. https://doi.org/10.1007/978-3-319-11900-7_42

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-11900-7_42

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11899-4

  • Online ISBN: 978-3-319-11900-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics