Skip to main content
Log in

An optimal control strategy for two-dimensional motion camouflage with non-holonimic constraints

  • Original Paper
  • Published:
Biological Cybernetics Aims and scope Submit manuscript

Abstract

Motion camouflage is a stealth behaviour observed both in hover-flies and in dragonflies. Existing controllers for mimicking motion camouflage generate this behaviour on an empirical basis or without considering the kinematic motion restrictions present in animal trajectories. This study summarises our formal contributions to solve the generation of motion camouflage as a non-linear optimal control problem. The dynamics of the system capture the kinematic restrictions to motion of the agents, while the performance index ensures camouflage trajectories. An extensive set of simulations support the technique, and a novel analysis of the obtained trajectories contributes to our understanding of possible mechanisms to obtain sensor based motion camouflage, for instance, in mobile robots.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Alexander RM (2003) Principles of animal locomotion. Princeton University Press, Princeton

    Google Scholar 

  • Anderson A (2003) Sensory motor neural systems for a predatory stealth behaviour camouflaging motion. PhD thesis, Computer Science, Queen Mary University of London

  • Anderson A, McOwan P (2003a) Humans deceived by predatory stealth strategy camouflaging motion. Proc R Soc Lond B 270(Suppl 1): S18

    Article  Google Scholar 

  • Anderson A, McOwan P (2003b) Model of a predatory stealth behaviour camouflaging motion. Proc R Soc B 270: 489–495

    Article  PubMed  Google Scholar 

  • Arechavaleta G, Laumond JP, Hicheur H, Berthoz A (2008) An optimality principle governing human walking. IEEE Trans Robot 24(1): 5–14

    Article  Google Scholar 

  • Boeddeker N, Egelhaaf M (2003) Steering a virtual blowfly: simulation of visual pursuit. Proc R Soc 270: 1971–1978

    Article  Google Scholar 

  • Carey N (2007) Biomimetic strategies for motion camouflage. PhD thesis, Australian National University

  • Carey N, Ford J, Chahl J (2004) Biologically inspired guidance for motion camouflage. In: Proceedings asian control conference 3, vol 3, pp 1793–1799

  • Firsby JB, Stone JV (2010) Seeing. The computational approach to biological vision. The MIT Press, Cambridge

    Google Scholar 

  • Fox D, Burgard W, Thrun S (1997) The dynamic window approach to collision avoidance. IEEE Robot Autom Mag 4(1): 23–33

    Article  Google Scholar 

  • Fraenkel G, Gunn D (1961) The orientation of animals. Kineses, taxes and compass reactions. Dover publications, New York

    Google Scholar 

  • Franceschini N, Pichon J, Blanes C, Brady J (1992) From insect vision to robot vision [and discussion]. Phil Trans R Soc Lond B 337: 283–294

    Article  Google Scholar 

  • Glendinning P (2003) The mathematics of motion camouflage. Proc R Soc B 271: 477–481

    Article  Google Scholar 

  • Justh EW, Krishnaprasad PS (2006) Steering laws for motion camouflage. Proc R Soc A 462: 3629–3643

    Article  Google Scholar 

  • Kirk D (2004) Optimal control theory. An introduction. Dover publications, New York

    Google Scholar 

  • Latombe JC (1991) Robot Motion planning. Kluwer, Norwell

    Book  Google Scholar 

  • McLeod P, Dienes Z (1993) Running to catch the ball. Nature 362: 23

    Article  PubMed  CAS  Google Scholar 

  • Mizutani A, Chahl J, Srinivasan M (2003) Insect behaviour: motion camouflage in dragonflies. Nature 423: 604

    Article  PubMed  CAS  Google Scholar 

  • Rañó I (2009) A steering taxis model and the qualitative analysis of its trajectories. Adapt Behav 17(3): 197–211

    Article  Google Scholar 

  • Rañó I, Burbridge C (2010) Motion camouflage for unicycle robots using optimal control. In: Proceedings of TAROS

  • Rañó I, Burbridge C (2011) Two dimensional motion camouflage for unicycle robots. In: International workshop on bio-inspired robots

  • Rañó I, Nehmzow U, Iglesias R (2009) Application of system identification to the implementation of motion camouflage in mobile robots. Tech. Rep. RR-09-01, Computer Sciences and Systems Engineering Dept. University of Zaragoza

  • Reddy PV, Justh EW, Krishnaprasad P (2006) Motion camouflage in three dimensions. In: IEEE conference on decision and control, pp 3327–3332

  • Reynolds C (1999) Steering behaviors for autonomous characters. In: Proceedings of the 1999 game developers conference. Miller Freeman Game Group, San Francisco, pp 763–782

  • Russell S, Norvig P (1996) Artificial intelligence. A modern approach. Prentice Hall, Englewood Cliffs

    Google Scholar 

  • Srinivasan M (1995) Strategies for visual navigation, target detection and camouflage: inspirations from insect vision. In: IEEE international conference on neural networks, vol 5, pp 2456–2460

  • Webb B (2000) What does robotics offer animal behaviour. Animal Behav 60: 545–558

    Article  Google Scholar 

  • Webb B (2001) A spiking neuron controller for robot phonotaxis. In: Consi TR, Webb B (eds) Biorobotics. The MIT/AAAI Press, Menlo Park, pp 3–20

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Iñaki Rañó.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rañó, I. An optimal control strategy for two-dimensional motion camouflage with non-holonimic constraints. Biol Cybern 106, 261–270 (2012). https://doi.org/10.1007/s00422-012-0493-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00422-012-0493-7

Keywords

Navigation