Advertisement

Body Symmetry in Morphologically Evolving Modular Robots

  • T. van de VeldeEmail author
  • C. Rossi
  • A. E. Eiben
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11454)

Abstract

Almost all animals natural evolution has produced on Earth have a symmetrical body. In this paper we investigate the evolution of body symmetry in an artificial system where robots evolve. To this end, we define several measures to quantify symmetry in modular robots and see how these relate to fitness that corresponds to a locomotion task. We find that, although there is only a weak correlation between symmetry and fitness over the course of a single evolutionary run, there is a positive correlation between the level of symmetry and maximum fitness when a set of runs is taken into account.

Keywords

Evolutionary robotics Modular robots Symmetry 

References

  1. 1.
    Eiben, A., Smith, J.: Introduction to Evolutionary Computing, 2nd edn. Springer, Heidelberg (2015).  https://doi.org/10.1007/978-3-662-05094-1
  2. 2.
    Eiben, A., Smith, J.: From evolutionary computation to the evolution of things. Nature 521(7553), 476–482 (2015)CrossRefGoogle Scholar
  3. 3.
    Bongard, J.C.: Evolutionary robotics. Commun. ACM 56(8), 74–83 (2013). http://doi.acm.org/10.1145/2493883
  4. 4.
    Floreano, D., Husbands, P., Nolfi, S.: Evolutionary robotics. In: Siciliano, B., Khatib, O. (eds.) Springer Handbook of Robotics, vol. Part G. 61, pp. 1423–1451. Springer, Heidelberg (2008).  https://doi.org/10.1007/978-3-540-30301-5_62
  5. 5.
    Sims, K.: Evolving 3D morphology and behavior by competition. Artif. Life 1(4), 353–372 (1994).  https://doi.org/10.1162/artl.1994.1.353
  6. 6.
    Sims, K.: Evolving virtual creatures. In: Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques SIGGRAPH 1994, pp. 15–22. ACM, New York (1994).  https://doi.org/10.1145/192161.192167
  7. 7.
    Lipson, H., Pollack, J.B.: Automatic design and manufacture of robotic lifeforms. Nature 406, 974–978 (2000)CrossRefGoogle Scholar
  8. 8.
    Auerbach, J., et al.: Robogen: robot generation through artificial evolution. In: Artificial Life 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems, pp. 136–137 (2014)Google Scholar
  9. 9.
    Brodbeck, L., Hauser, S., Iida, F.: Morphological evolution of physical robots through model-free phenotype development. PLoS One 10(6), e0128444 (2015)CrossRefGoogle Scholar
  10. 10.
    Eiben, A.E., Kernbach, S., Haasdijk, E.: Embodied artificial evolution - artificial evolutionary systems in the 21st century. Evol. Intell. 5(4), 261–272 (2012). http://www.few.vu.nl/~ehaasdi/papers/EAE-manifesto.pdf
  11. 11.
    Eiben, A.E., et al.: The triangle of life: Evolving robots in real-time and real-space (2013)Google Scholar
  12. 12.
    Eiben, A.E.: EvoSphere: the world of robot evolution. In: Dediu, A.-H., Magdalena, L., Martín-Vide, C. (eds.) TPNC 2015. LNCS, vol. 9477, pp. 3–19. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-26841-5_1CrossRefGoogle Scholar
  13. 13.
    Hupkes, E., Jelisavcic, M., Eiben, A.E.: Revolve: a versatile simulator for online robot evolution. In: Sim, K., Kaufmann, P. (eds.) EvoApplications 2018. LNCS, vol. 10784, pp. 687–702. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-77538-8_46CrossRefGoogle Scholar
  14. 14.
    Jelisavcic, M., et al.: Real-world evolution of robot morphologies: a proof of concept. In: Artificial Life (2017)Google Scholar
  15. 15.
    Werner, E.: The origin, evolution and development of bilateral symmetry in multicellular organisms. Quantitative Biology ArXiv:1207.3289 (2012)
  16. 16.
    Marbach, D., Ijspeert, A.J.: Online optimization of modular robot locomotion. In: IEEE International Conference Mechatronics and Automation 2005, vol. 1, pp. 248–253, July 2005Google Scholar
  17. 17.
    Faiña, A., Bellas, F., López Peña, F., Duro, R.: Edhmor: evolutionary designer of heterogeneous modular robots. Eng. Appl. Artif. Intell. 26, 2408–2423 (2013)Google Scholar
  18. 18.
    Cheney, N., MacCurdy, R., Clune, J., Lipson, H.: Unshackling evolution: Evolving soft robots with multiple materials and a powerful generative encoding. In: Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation GECCO 2013, pp. 167–174. ACM, New York (2013).  https://doi.org/10.1145/2463372.2463404
  19. 19.
    Clune, J., Beckmann, B.E., Ofria, C., Pennock, R.T.: Evolving coordinated quadruped gaits with the hyperneat generative encoding. In: 2009 IEEE Congress on Evolutionary Computation, pp. 2764–2771, May 2009Google Scholar
  20. 20.
    Sun, C., Sherrah, J.: 3D symmetry detection using the extended gaussian image. IEEE Trans. Pattern Anal. Mach. Intell. 19(2), 164–168 (1997)CrossRefGoogle Scholar
  21. 21.
    Mitra, N.J., Guibas, L.J., Pauly, M.: Partial and approximate symmetry detection for 3D geometry. ACM Trans. Graph. 25(3), 560–568, July 2006.  https://doi.org/10.1145/1141911.1141924
  22. 22.
    Li, W.H., Zhang, A.M., Kleeman, L.: Bilateral symmetry detection for real-time robotics applications. Int. J. Robot. Res. 27(7), 785–814 (2008).  https://doi.org/10.1177/0278364908092131
  23. 23.
    Zabrodsky, H., Peleg, S., Avnir, D.: A measure of symmetry based on shape similarity. In: Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 703–706, June 1992Google Scholar
  24. 24.
    Zabrodsky, H., Peleg, S., Avnir, D.: Symmetry as a continuous feature. IEEE Trans. Pattern Anal. Mach. Intell. 17(12), 1154–1166 (1995)CrossRefGoogle Scholar
  25. 25.
    Miras, K., Haasdijk, E., Glette, K., Eiben, A.E.: Search space analysis of evolvable robot morphologies. In: Sim, K., Kaufmann, P. (eds.) EvoApplications 2018. LNCS, vol. 10784, pp. 703–718. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-77538-8_47CrossRefGoogle Scholar
  26. 26.
    Rossi, C., Eiben, A.: Simultaneous versus incremental learning of multiple skills by modular robots. Evol. Intell. 7(2), 119–131 (2014)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of AmsterdamAmsterdamThe Netherlands
  2. 2.Centre for Automation and Robotics UPM-CSICMadridSpain
  3. 3.Vrije Universiteit AmsterdamAmsterdamThe Netherlands

Personalised recommendations