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Predator Evasion by a Robocrab

  • Theodoros Stouraitis
  • Evripidis Gkanias
  • Jan M. Hemmi
  • Barbara WebbEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10384)

Abstract

We describe the first robot designed to emulate specific perceptual and motor capabilities of the fiddler crab. An omnidirectional robot platform uses onboard computation to process images from a \(360^{\circ }\) camera view, filtering it through a biological model of the crab’s ommatidia layout, extracting potential ‘predator’ cues, and executing an evasion response that also depends on contextual information. We show that, as for real crabs, multiple cues are needed for effective escape in different predator-prey scenarios.

References

  1. 1.
    Borenstein, J., Feng, L.: Gyrodometry: A new method for combining data from gyros and odometry in mobile robots. In: IEEE Robotics and Automation, vol. 1, pp. 423–428 (1996)Google Scholar
  2. 2.
    Hemmi, J.M.: Predator avoidance in fiddler crabs: 1. Escape decisions in relation to the risk of predation. Anim. Behav. 69(3), 603–614 (2005)CrossRefGoogle Scholar
  3. 3.
    Hemmi, J.M.: Predator avoidance in fiddler crabs: 2. The visual cues. Anim. Behav. 69(3), 615–625 (2005)CrossRefGoogle Scholar
  4. 4.
    Hemmi, J.M., Pfeil, A.: A multi-stage anti-predator response increases information on predation risk. J. Exp. Biol. 213(9), 1484–1489 (2010)CrossRefGoogle Scholar
  5. 5.
    Hemmi, J.M., Tomsic, D.: The neuroethology of escape in crabs: from sensory ecology to neurons and back. Curr. Opin. Neurobiol. 22(2), 194–200 (2012)CrossRefGoogle Scholar
  6. 6.
    Land, M., Layne, J.: The visual control of behaviour in fiddler crabs: I. Resolution, thresholds and the role of the horizon. J. Comp. Physiol. A. 177(1), 81–90 (1995)CrossRefGoogle Scholar
  7. 7.
    Land, M., Layne, J.: The visual control of behaviour in fiddler crabs: II. Tracking control systems in courtship and defence. J. Comp. Physiol. A 177(1), 91–103 (1995)CrossRefGoogle Scholar
  8. 8.
    Layne, J., Barnes, W.J.P., Duncan, L.M.J.: Mechanisms of homing in the fiddler crab Uca rapax 1. Spatial and temporal characteristics of a system of small-scale navigation. J. Exp. Biol. 206(24), 4413–4423 (2003)CrossRefGoogle Scholar
  9. 9.
    Layne, J., Barnes, W.J.P., Duncan, L.M.J.: Mechanisms of homing in the fiddler crab Uca rapax 2. Information sources and frame of reference for a path integration system. J. Exp. Biol. 206(24), 4425–4442 (2003)CrossRefGoogle Scholar
  10. 10.
    Nagatani, K., Tachibana, S., Sofne, M., Tanaka, Y.: Improvement of odometry for omnidirectional vehicle using optical flow information. In: Proceedings of the 2000 IEEE/RSJ International Conference on IROS 2000, vol. 1, pp. 468–473 (2000)Google Scholar
  11. 11.
    Oliva, D., Tomsic, D.: Visuo-motor transformations involved in the escape response to looming stimuli in the crab Neohelice (= Chasmagnathus) granulata. J. Exp. Biol. 215(19), 3488–3500 (2012)CrossRefGoogle Scholar
  12. 12.
    Raderschall, C.A., Magrath, R.D., Hemmi, J.M.: Habituation under natural conditions: model predators are distinguished by approach direction. J. Exp. Biol. 214(24), 4209–4216 (2011)CrossRefGoogle Scholar
  13. 13.
    Rojas, R., Förster, A.G.: Holonomic control of a robot with an omnidirectional drive. KI-Künstliche Intelligenz 20(2), 12–17 (2006)Google Scholar
  14. 14.
    Sandeman, D.C.: Dynamic receptors in the statocysts of crabs. Fortschritte der Zoologie 23(1), 185 (1975)Google Scholar
  15. 15.
    Smolka, J., Hemmi, J.M.: Topography of vision and behaviour. J. Exp. Biol. 212(21), 3522–3532 (2009)CrossRefGoogle Scholar
  16. 16.
    Smolka, J., Zeil, J., Hemmi, J.M.: Natural visual cues eliciting predator avoidance in fiddler crabs. Proc. Roy. Soc. Lond. B: Biol. Sci. 278(1724), 3584–3592 (2011)CrossRefGoogle Scholar
  17. 17.
    Tomsic, D., de Astrada, M., Sztarker, J., Maldonado, H.: Behavioral and neuronal attributes of short-and long-term habituation in the crab Chasmagnathus. Neurobiol. Learn. Memory 92(2), 176–182 (2009)CrossRefGoogle Scholar
  18. 18.
    Tsai, C., Tai, F., Lee, Y.: Motion controller design and embedded realization for mecanum wheeled omnidirectional robots. In: 2011 9th World Congress on Intelligent Control and Automation (WCICA), pp. 546–551. IEEE (2011)Google Scholar
  19. 19.
    Viboonchaicheep, P., Shimada, A., Kosaka, Y.: Position rectification control for mecanum wheeled omni-directional vehicles. In: The 29th Annual Conference of the IEEE Industrial Electronics Society, IECON 2003, vol. 1, pp. 854–859. IEEE (2003)Google Scholar
  20. 20.
    Yi, J., Zhang, J., Song, D., Jayasuriya, S.: IMU-based localization and slip estimation for skid-steered mobile robots. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007, pp. 2845–2850. IEEE (2007)Google Scholar
  21. 21.
    Zeil, J., Hemmi, J.M.: The visual ecology of fiddler crabs. J. Comp. Physiol. A. 192(1), 1–25 (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Theodoros Stouraitis
    • 1
  • Evripidis Gkanias
    • 1
  • Jan M. Hemmi
    • 2
  • Barbara Webb
    • 1
    Email author
  1. 1.School of Informatics, Institute of Perception, Action and BehaviourUniversity of EdinburghEdinburghUK
  2. 2.School of Biological SciencesUniversity of Western AustraliaCrawleyAustralia

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