Skip to main content
SpringerLink
Log in

A Spiking Model of Desert Ant Navigation Along a Habitual Route

  • Conference paper
  • First Online:
Recent Advances in Soft Computing (MENDEL 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 837))

Included in the following conference series:

  • 337 Accesses

Abstract

A model producing behavior mimicking that of a homing desert ant while approaching the nest along a habitual route is presented. The model combines two strategies that interact with each other: local vector navigation and landmark guidance with an average landmark vector. As a multi-segment route with several waypoints is traversed, local vector navigation is mainly used when leaving a waypoint, landmark guidance is mostly used when approaching a waypoint, and a weighted interplay of the two is used in between waypoints. The model comprises a spiking neural network that is developed based on the principles of the Neural Engineering Framework. Its performance is demonstrated with a simulated robot in a virtual environment, which is shown to successfully navigate to the final waypoint in different scenes.

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ardin, P., Peng, F., Mangan, M., Lagogiannis, K., Webb, B.: Using an insect mushroom body circuit to encode route memory in complex natural environments. PLoS Comput. Biol. 12, e1004683 (2016). https://doi.org/10.1371/journal.pcbi.1004683

    Article  Google Scholar 

  2. Baddeley, B., Graham, P., Husbands, P., Philippides, A.: A model of ant route navigation driven by scene familiarity. PLoS Comput. Biol. 8, e1002336 (2012). https://doi.org/10.1371/journal.pcbi.1002336

    Article  Google Scholar 

  3. Bekolay, T., Bergstra, J., Hunsberger, E., DeWolf, T., Stewart, T.C., Rasmussen, D., Choo, X., Voelker, A.R., Eliasmith, C.: Nengo: a Python tool for building large-scale functional brain models. Front. Neuroinform. 7, 48 (2014). https://doi.org/10.3389/fninf.2013.00048

    Article  Google Scholar 

  4. Bregy, P., Sommer, S., Wehner, R.: Nest-mark orientation versus vector navigation in desert ants. J. Exp. Biol. 211, 1868–1873 (2008). https://doi.org/10.1242/jeb.018036

    Article  Google Scholar 

  5. Collett, M.: How desert ants use a visual landmark for guidance along a habitual route. In: Proceedings of the National Academy of Sciences U.S.A., vol. 107, pp. 11638–11643 (2010). https://doi.org/10.1073/pnas.1001401107

  6. Collett, M., Collett, T.S., Bisch, S., Wehner, R.: Local and global vectors in desert ant navigation. Nature 394, 269–272 (1998)

    Article  Google Scholar 

  7. Cruse, H., Wehner, R.: No need for a cognitive map: decentralized memory for insect navigation. PLoS Comput. Biol. 7, e1002009 (2011). https://doi.org/10.1371/journal.pcbi.1002009

    Article  Google Scholar 

  8. Eliasmith, C., Anderson, C.: Neural Engineering: Computation, Representation, and Dynamics in Neurobiological Systems. MIT Press, Cambridge (2003)

    Google Scholar 

  9. Lambrinos, D., Möller, R., Labhart, T., Pfeifer, R., Wehner, R.: A mobile robot employing insect strategies for navigation. Rob. Auton. Syst. 30, 39–64 (2000). https://doi.org/10.1016/S0921-8890(99)00064-0

    Article  Google Scholar 

  10. Rohmer, E., Singh, S.P.N., Freese, M.: V-REP: a versatile and scalable robot simulation framework. In: 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1321–1326, Tokyo (2013). https://doi.org/10.1109/IROS.2013.6696520

  11. Smith, L., Philippides, A., Graham, P., Baddeley, B., Husbands, P.: Linked local navigation for visual route guidance. Adapt. Behav. 15, 257–271 (2007). https://doi.org/10.1177/1059712307082091

    Article  Google Scholar 

  12. Stewart, T.C., Choo, X., Eliasmith, C.: Dynamic behaviour of a spiking model of action selection in the basal ganglia. In: Salvucci, D.D., Gunzelmann, G. (eds.) Proceedings of the 10th International Conference on Cognitive Modeling, pp. 235–240, Philadelphia (2010)

    Google Scholar 

  13. Strausfeld, N.J., Hirth, F.: Deep homology of arthropod central complex and vertebrate basal ganglia. Science 340, 157–161 (2013). https://doi.org/10.1126/science.1231828

    Article  Google Scholar 

  14. Wehner, R.: Desert ant navigation: how miniature brains solve complex tasks. J. Comp. Physiol. A. 189, 579–588 (2003). https://doi.org/10.1007/s00359-003-0431-1

    Article  Google Scholar 

  15. Wehner, R.: The architecture of the desert ant’s navigational toolkit (Hymenoptera: Formicidae). Myrmecol. News 12, 85–96 (2009)

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Information Technology, Lodz University of Technology, Lodz, Poland

    Przemyslaw Nowak

  2. Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, ON, Canada

    Terrence C. Stewart

Authors
  1. Przemyslaw Nowak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Terrence C. Stewart
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Przemyslaw Nowak .

Editor information

Editors and Affiliations

  1. Department of Applied Computer Science, Institute of Automation and Computer Science, Faculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic

    Radek Matoušek

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nowak, P., Stewart, T.C. (2019). A Spiking Model of Desert Ant Navigation Along a Habitual Route. In: Matoušek, R. (eds) Recent Advances in Soft Computing . MENDEL 2017. Advances in Intelligent Systems and Computing, vol 837. Springer, Cham. https://doi.org/10.1007/978-3-319-97888-8_18

Download citation

Publish with us

Policies and ethics

Search

Navigation