Skip to main content

Organising Bodyformation of Modular Autonomous Robots Using Virtual Embryogenesis

  • Conference paper
  • First Online:
New Trends in Medical and Service Robots (MESROB 2016)

Part of the book series: Mechanisms and Machine Science ((Mechan. Machine Science,volume 48))

Included in the following conference series:

Abstract

In this paper the ability of Virtual Embryogenesis system (VE) to initiate and facilitate the build process of a multi-robot organism is presented. According to a single genome, which is spread in the whole organism, substances (morphogenes) are diffused to all neighbouring robots within the organism and new modules are recruited to advance the building process. Different shapes can be built by this system using different, pre-evolved genomes. This ability to build a robotic modular organism is very stable and is not influenced by the environment the controlling genome has evolved in. The presented method is suggested to control modular robots in future applications in dynamic environments, e.g., in interaction with humans.

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

Access this chapter

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
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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. Carroll, S.B.: Endless forms: the evolution of gene regulation and morphological diversity. Cell 101(6), 577–580 (2000)

    Article  Google Scholar 

  2. Carroll, S.B.: Endless Forms Most Beautiful: The New Science of Evo Devo. W. W. Norton (2006)

    Google Scholar 

  3. Crick, F.: Diffusion in embryogenesis. Nature 225(5231), 420–422 (1970). doi:10.1038/225420a0

    Article  Google Scholar 

  4. Dauschan, M., Thenius, R., Schmickl, T., Crailsheim, K.: Using virtual embryogenesis multi-robot organisms. In: International Conference on Adaptive and Intelligent Systems, ICAIS’11, Klagenfurt, AT, 06–08 Sept 2011. Proceedings, pp. 238–247 (2011)

    Google Scholar 

  5. Dorigo, M., Tuci, E., Groß, R., Trianni, V., Labella, T.H., Nouyan, S., Ampatzis, C., Deneubourg, J.L., Baldassarre, G., Nolfi, S., Mondada, F., Floreano, D., Gambardella, L.M.: The SWARM-BOTS project. In: Proceeding of Swarm Robotics, SAB 2004 International Workshop, Santa Monica, pp. 31–44. Springer (2005). http://www.springerlink.com/content/e4klufrqeqe6nvc2

  6. Ephrussi, A., Johnston, D.S.: Seeing is believing—the bicoid morphogen gradient matures. Cell 116(2), 143–152 (2004). doi:10.1016/S0092-8674(04)00037-6

    Article  Google Scholar 

  7. Gomperts, B.D., Kramer, I.M., Tatham, P.E.R.: Signal Transduction. Academic Press (2002)

    Google Scholar 

  8. Gurdon, J.B., Bourillot, P.Y.: Morphogen gradient interpretation. Nature 413(6858), 797–803 (2001). doi:10.1038/35101500

    Article  Google Scholar 

  9. Jin, Y., Schramm, L., Sendhoff, B.: A gene regulatory model for the development of primitive nervous systems. In: Proceedings of the 15th International Conference on Advances in Neuro-Information Processing—Volume Part I, ICONIP’08, pp. 48–55. Springer, Berlin (2009)

    Google Scholar 

  10. Kernbach, S., Hamann, H., Stradner, J., Thenius, R., Schmickl, T., Crailsheim, K., van Rossum, A., Sebag, M., Bredeche, N., Yao, Y., Baele, G., de Peer, Y.V., Timmis, J., Mohktar, M., Tyrrell, A., Eiben, A., McKibbin, S., Liu, W., Winfield, A.F.: On adaptive self-organization in artificial robot organisms. In: The First International Conference on Adaptive and Self-adaptive Systems and Applications (ADAPTIVE’09). IEEE Press (2009)

    Google Scholar 

  11. Kernbach, S., Schmickl, T., Hamann, H., Stradner, J., Schwarzer, C., Schlachter, F., Winfield, A.F., Matthias, R.: Adaptive action selection mechanisms for evolutionary multimodular robotics. In: Fellermann, H., Dörr, M., Hanczyc, M.M., Laursen, L.L., Maurer, S., Merkle, D., Monnard, P.A., Støy, K., Rasmussen, S. (eds.) Artificial Life XII (ALife XII), pp. 781–788. MIT Press (2010)

    Google Scholar 

  12. Kernbach, S., Scholz, O., Harada, K., Popesku, S., Liedke, J., Raja, H., Liu, W., Caparrelli, F., Jemai, J., Havlik, J., Meister, E., Levi, P.: Multi-robot organisms: state of the art. In: ICRA10, workshop on “Modular Robots: State of the Art”, Anchorage (2010)

    Google Scholar 

  13. Kornienko, S., Kornienko, O., Nagarathinam, A., Levi, P.: From real robot swarm to evolutionary multi-robot organism. In: Srinivasan, D., Wang, L. (eds.) 2007 IEEE Congress on Evolutionary Computation, pp. 1483–1490. IEEE (2007). http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4424647

  14. Levi, P., Kernbach, S. (eds.): Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution. Springer (2010)

    Google Scholar 

  15. Mondada, F., Floreano, D., Gambardella, L.M.: The SWARM-BOTS project. Lect. Notes Comput. Sci. 3342, 31–44 (2005)

    Article  Google Scholar 

  16. Moran, I.F., Moreno, A., Merelo, J., Chacon, P. (eds.): Noise and the Reality Gap: The Use of Simulation in Evolutionary Robotics. Springer (1995)

    Google Scholar 

  17. Müller, G.B.: Evo-devo: extending the evolutionary synthesis. Nat. Rev. Genet. 8, 943–949 (2007)

    Article  Google Scholar 

  18. Näär, A.M., Lemon, B., Tjian, R.: Transcriptional coactivator complexes. Annu. Rev. Biochem. 70, 475–501 (2001)

    Article  Google Scholar 

  19. REPLICATOR: Project website (2012). http://www.replicators.eu

  20. Roggen, D., Federici, D., Floreano, D.: Evolutionary morphogenesis for multi-cellular systems. Genet. Program. Evolvable Mach. 8, 61–96 (2007). doi:10.1007/s10710-006-9019-1

    Article  Google Scholar 

  21. Rubenstein, M., Shen, W.M.: Scalable self-assembly and self-repair in a collective of robots. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), St. Louis, Missouri, USA (2009)

    Google Scholar 

  22. Rubenstein, M., Shen, W.M.: Automatic scalable size selection for the shape of a distributed robotic collective. In: iros-10, pp. 508–513 (2010)

    Google Scholar 

  23. Rumbaugh, J., Blaha, M., Premerlani, W., Eddy, F., Lorenson, W.: Object-Oriented Modeling and Design, 1st edn. Prentice Hall, Inc. (1991)

    Google Scholar 

  24. Schmickl, T., Thenius, R., Stradner, J., Hamann, H., Crailsheim, K.: Robotic organisms: artificial homeostatic hormone system and virtual embryogenesis as examples for adaptive reaction-diffusion controllers. In: Kernbach, S., Fitch R. (eds.) IROS 2011 Workshop–Reconfigurable Modular Robotics: Challenges of Mechatronic and Bio-Chemo-Hybrid Systems (2011)

    Google Scholar 

  25. Schramm, L., Jin, Y., Sendhoff, B.: Evolutionary synthesis and analysis of a gene regulatory network for dynamically stable growth and regeneration. BioSystems (2010). Submitted

    Google Scholar 

  26. Shvartsman, S.Y., Coppey, M., Berezhkovskii, A.M.: Dynamics of maternal morphogen gradients in drosophila. Curr. Opin. Genet. Dev. 18(4), 342–347 (2008)

    Article  Google Scholar 

  27. Stradner, J., Thenius, R., Zahadat, P., Hamann, H., Crailsheim, K., Schmickl, T.: Algorithmic requirements for swarm intelligence in differently coupled collective systems. Chaos, Solitons Fractals (2013). Accepted for publication

    Google Scholar 

  28. Stroustrup, B.: The C++ Programming Language, 3rd edn. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA (2000)

    MATH  Google Scholar 

  29. SYMBRION: Project website (2012). http://www.symbrion.eu

  30. Thenius, R., Bodi, M., Schmickl, T., Crailsheim, K.: Evolving virtual embryogenesis to structure complex controllers. PerAdaMagazine (2009). doi:10.2417/2201009.003291

    MATH  Google Scholar 

  31. Thenius, R., Bodi, M., Schmickl, T., Crailsheim, K.: Growth of structured artificial neural networks by virtual embryogenesis. In: Kampis, G., Karsai, I., Szathmáry, E. (eds.) ECAL (2), Lecture Notes in Computer Science, vol. 5778, pp. 118–125. Springer (2009)

    Google Scholar 

  32. Thenius, R., Bodi, M., Schmickl, T., Crailsheim, K.: Evolving artificial neural networks and artificial embryology. In: Levi, P., Kernbach, S. (eds.) Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution, pp. 266–268. Springer (2010). doi:10.1007/978-3-642-14547-6

  33. Thenius, R., Bodi, M., Schmickl, T., Crailsheim, K.: Using virtual embryogenesis for structuring controllers. In: Hart, E., McEwan, C., Timmis, J., Hone, A. (eds.) 9th International Conference on Artificial Immune Systems, ICARIS 2010, Edinburgh, UK, 26–29 July 2010. Proceedings, Lecture Notes in Computer Science, vol. 6209, pp. 312–313. Springer (2010). doi:10.1007/978-3-642-14547-6_27

  34. Thenius, R., Dauschan, M., Schmickl, T., Crailsheim, K.: Regenerative abilities in modular robots using virtual embryogenesis. In: International Conference on Adaptive and Intelligent Systems, ICAIS’11, Klagenfurt, AT, 06–08 Sept 2011. Proceedings, pp. 227–237 (2011)

    Google Scholar 

  35. Thenius, R., Schmickl, T., Crailsheim, K.: Novel concept of modelling embryology for structuring an artificial neural network. In: Troch, I., Breitenecker, F. (eds.) Proceedings of the MATHMOD, pp. 1821–1831 (2009)

    Google Scholar 

  36. Turing, A.M.: The chemical basis of morphogenesis. Philos. Trans. R. Soc. Lond. Ser. B, Biol. Sci. B237(641), 37–72 (1952)

    Google Scholar 

  37. Ungerer, G., Dionne, J., Durant, M.: uClinux: Embedded Linux/Microcontroller Project (2008). http://www.uclinux.org

  38. Weatherbee, S.D., Carroll, S.B.: Selector genes and limb identity in arthropods and vertebrates. Cell 97(3), 283–286 (1999)

    Article  Google Scholar 

  39. Wilensky, U.: Netlogo. Center for Connected Learning and Computer-Based Modeling, Northwestern University. Evanston, IL (1999). http://ccl.northwestern.edu/netlogo/

  40. Wolpert, L.: Positional information and the spatial pattern of cellular differentiation. J. Theor. Biol. 25(1), 1–47 (1969)

    Article  Google Scholar 

  41. Wolpert, L.: One hundred years of positional information. Trends Genet. 12(9), 359–364 (1996). http://view.ncbi.nlm.nih.gov/pubmed/8855666

  42. Wolpert, L.: Principles of Development. Oxford University Press (1998)

    Google Scholar 

Download references

Acknowledgements

This work was supported by: EU-ICT project REPLICATOR, no. 216240; EU H2020 FET-Proactive project ‘subCULTron’, no. 640967.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to R. Thenius .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Daushan, M., Thenius, R., Crailsheim, K., Schmickl, T. (2018). Organising Bodyformation of Modular Autonomous Robots Using Virtual Embryogenesis. In: Husty, M., Hofbaur, M. (eds) New Trends in Medical and Service Robots. MESROB 2016. Mechanisms and Machine Science, vol 48. Springer, Cham. https://doi.org/10.1007/978-3-319-59972-4_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-59972-4_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59971-7

  • Online ISBN: 978-3-319-59972-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics