Biologically–Inspired Motion Pattern Design of Multi–legged Creatures

  • Shihui Guo
  • Safa Tharib
  • Jian Chang
  • Jianjun Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7834)

Abstract

In this paper, we propose a novel strategy to synthesize motion patterns for multi–legged creatures inspired by the biological knowledge. To prove the concept, our framework deploys an approach of coupling the dynamics model, the Inverted Pendulum Model, and the biological controller, the Central Pattern Generator, to synthesize the motion of multiple legged creatures. The dynamics model ensures the physical plausibility and allows the virtual character to react to the external perturbations, where the biological controller coordinates the motion of several legs with designed numerical operators, providing user-friendly high–level control. This novel framework is computationally efficient by taking advantages of the self-similarity in motion and able to animate characters with different skeletons.

Keywords

Computer Animation Character Motion Multi–legged Creatures 

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References

  1. 1.
    Altendorfer, R., Moore, N., Komsuoglu, H., Buehler, M., Brown, H., McMordie, D., Saranli, U., Full, R., Koditschek, D.: Rhex: A biologically inspired hexapod runner. Autonomous Robots 11, 207–213 (2001), doi:10.1023/A:1012426720699MATHCrossRefGoogle Scholar
  2. 2.
    Chung, S.J., Dorothy, M.: Neurobiologically Inspired Control of Engineered Flapping Flight. ArXiv e-prints (May 2009)Google Scholar
  3. 3.
    Coros, S., Karpathy, A., Jones, B., Reveret, L., van de Panne, M.: Locomotion skills for simulated quadrupeds. ACM Trans. Graph. 30, 59:1–59:12 (2011), http://doi.acm.org/10.1145/2010324.1964954 Google Scholar
  4. 4.
    Favreau, L., Reveret, L., Depraz, C., Cani, M.P.: Animal gaits from video: comparative studies. Graph. Models 68, 212–234 (2006)CrossRefGoogle Scholar
  5. 5.
    Full, R.J., Tu, M.S.: Mechanics of a rapid running insect: two-, four- and six-legged locomotion. Journal of Experimental Biology 156(1), 215–231 (1991)Google Scholar
  6. 6.
    Geijtenbeek, T., Pronost, N., Egges, A., Overmars, M.H.: Interactive character animation using simulated physics. Eurographics - State of the Art Reports (2011)Google Scholar
  7. 7.
    Gibson, D.P., Oziem, D.J., Dalton, C.J., Campbell, N.W.: Capture and synthesis of insect motion. In: Proceedings of the 2005 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, SCA 2005, pp. 39–48. ACM, New York (2005)CrossRefGoogle Scholar
  8. 8.
    Gibson, D., Campbell, N., Thomas, B.: Quadruped gait analysis using sparse motion information. In: International Conference on Image Processing. IEEE Computer Society (September 2003)Google Scholar
  9. 9.
    Ijspeert, A.: Central pattern generators for locomotion control in animals and robots: A review. Neural Networks 21(4), 642–653 (2008), http://dx.doi.org/10.1016/j.neunet.2008.03.014 CrossRefGoogle Scholar
  10. 10.
    Jain, S., Ye, Y., Liu, C.K.: Optimization-based interactive motion synthesis. ACM Trans. Graph, 28(1), 10:1–10:12 (2009)Google Scholar
  11. 11.
    Kovar, L., Gleicher, M., Pighin, F.: Motion graphs. In: ACM SIGGRAPH 2008 Classes, SIGGRAPH 2008, pp. 51:1–51:10. ACM, New York (2008)Google Scholar
  12. 12.
    de Lasa, M., Mordatch, I., Hertzmann, A.: Feature-based locomotion controllers. ACM Trans. Graph 29(4), 131:1–131:10 (2010)Google Scholar
  13. 13.
    Li, Y., Wang, T., Shum, H.Y.: Motion texture: a two-level statistical model for character motion synthesis. ACM Trans. Graph. 21(3), 465–472 (2002)CrossRefGoogle Scholar
  14. 14.
    Macchietto, A., Zordan, V., Shelton, C.R.: Momentum control for balance. ACM Trans. Graph 28, 80:1–80:8 (2009)Google Scholar
  15. 15.
    Marsden, J.E., McCracken, M.: The Hopf Bifurcation and Its Applications. Springer, New York (1976)MATHCrossRefGoogle Scholar
  16. 16.
    Mellen, N., Kiemel, T., Cohen, A.H.: Correlational analysis of fictive swimming in the lamprey reveals strong functional intersegmental coupling. Journal of Neurophysiology 73(3), 1020–1030 (1995)Google Scholar
  17. 17.
    Mojdehi, A., Alitavoli, M., Darvizeh, A.: Kinematic simulation of spider’s walking by image processing. In: Second International Conference on Information and Computing Science, ICIC 2009, vol. 2, pp. 3–6 (May 2009)Google Scholar
  18. 18.
    Pejsa, T., Pandzic, I.: State of the art in example-based motion synthesis for virtual characters in interactive applications. Computer Graphics Forum 29(1), 202–226 (2010)CrossRefGoogle Scholar
  19. 19.
    Righetti, L., Ijspeert, A.: Programmable central pattern generators: an application to biped locomotion control. In: Proceedings 2006 IEEE International Conference on Robotics and Automation, ICRA 2006, pp. 1585–1590 (May 2006)Google Scholar
  20. 20.
    Skrba, L., Revéret, L., Hétroy, F., Cani, M.P., O’sullivan, C.: Quadruped animation. In: Eurographics 2008, State-of-the-Art Report, EG-STAR, pp. 7–23. Eurographics Association, Crete (2008)Google Scholar
  21. 21.
    Steven, S.: Nonlinear dynamics and chaos with applications to physics, biology, chemistry and engineering. Westview Press (1994)Google Scholar
  22. 22.
    Taga, G., Yamaguchi, Y., Shimizu, H.: Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment. Biological Cybernetics 65, 147–159 (1991), http://dx.doi.org/10.1007/BF00198086, doi:10.1007/BF00198086MATHCrossRefGoogle Scholar
  23. 23.
    Taga, G.: A model of the neuro-musculo-skeletal system for human locomotion. Biological Cybernetics 73, 97–111 (1995), http://dx.doi.org/10.1007/BF00204048, doi:10.1007/BF00204048MATHCrossRefGoogle Scholar
  24. 24.
    Tsai, Y.Y., Lin, W.C., Cheng, K., Lee, J., Lee, T.Y.: Real-time physics-based 3d biped character animation using an inverted pendulum model. IEEE Transactions on Visualization and Computer Graphics 16(2), 325–337 (2010)CrossRefGoogle Scholar
  25. 25.
    Wang, J.M., Fleet, D.J., Hertzmann, A.: Optimizing walking controllers. ACM Trans. Graph. 28(5), 168:1–168:8 (2009)Google Scholar
  26. 26.
    Yin, K., Loken, K., van de Panne, M.: Simbicon: simple biped locomotion control. ACM Trans. Graph. 26(3) (July 2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Shihui Guo
    • 1
  • Safa Tharib
    • 1
  • Jian Chang
    • 1
  • Jianjun Zhang
    • 1
  1. 1.National Centre for Computer AnimationBournemouth UniversityUK

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