Programmable Self-assembly with Chained Soft Cells: An Algorithm to Fold into 2-D Shapes

  • Jürg Germann
  • Joshua Auerbach
  • Dario Floreano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8575)


Programmable self-assembly of chained modules holds potential for the automatic shape formation of morphologically adapted robots. However, current systems are limited to modules of uniform rigidity, which restricts the range of obtainable morphologies and thus the functionalities of the system. To address these challenges, we previously introduced “soft cells” as modules that can obtain different mechanical softness pre-setting. We showed that such a system can obtain a higher diversity of morphologies compared to state-of-the-art systems and we illustrated the system’s potential by demonstrating the self-assembly of complex morphologies. In this paper, we extend our previous work and present an automatic method that exploits our system’s capabilities in order to find a linear chain of soft cells that self-folds into a target 2-D shape.


Self-Assembly Soft Robotics Modular Robotics 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Murata, S., Kurokawa, H.: Self-Organizing Robots. Springer Tracts in Advanced Robotics, vol. 77 (2012)Google Scholar
  2. 2.
    Whitesides, G.M., Grzybowski, B.: Self-assembly at all scales. Science 295, 2418–2421 (2002)CrossRefGoogle Scholar
  3. 3.
    Pelesko, J.A.: Self assembly: the science of things that put themselves together. CRC Press (2007)Google Scholar
  4. 4.
    Gross, R., Dorigo, M.: Self-Assembly at the Macroscopic Scale. Proceedings of the IEEE 96, 1490–1508 (2008)CrossRefGoogle Scholar
  5. 5.
    Pfeifer, R., Lungarella, M., Iida, F.: Self-Organization, Embodiment, and Biologically Inspired Robotics. Science 318, 1088–1093 (2007)CrossRefGoogle Scholar
  6. 6.
    Griffith, S.: Growing Machines. PhD Thesis. MIT (2004)Google Scholar
  7. 7.
    Cheung, K.C., Demaine, E.D., Bachrach, J.R., Griffith, S.: Programmable assembly with universally foldable strings (Moteins). IEEE Transactions on Robotics 27, 718–729 (2011)CrossRefGoogle Scholar
  8. 8.
    Knaian, A.N., Cheung, K.C., Lobovsky, M.B., Oines, A.J., Schmidt-Neilsen, P., Gershenfeld, N.A.: The milli-motein: A self-folding chain of programmable matter with a one centimeter module pitch. In: IEEE International Conference on Intelligent Robots and Systems, pp. 1447–1453 (2012)Google Scholar
  9. 9.
    Yim, S., Sitti, M.: SoftCubes: Towards a Soft Modular Matter. In: IEEE International Conference on Robotics and Automation, pp. 530–536 (2013)Google Scholar
  10. 10.
    Risi, S., Cellucci, D., Lipson, H.: Ribosomal Robots: Evolved Designs Inspired by Protein Folding. In: GECCO 2013, pp. 263–270 (2013)Google Scholar
  11. 11.
    Germann, J., Maesani, A., Pericet-Camara, R., Floreano, D.: Soft Cells for Programmable Self-Assembly of Robotic Modules (Under review)Google Scholar
  12. 12.
    Germann, J., Maesani, A., Stöckli, Floreano, D.: Soft Cell Simulator: A tool to study Soft Multi-Cellular Robots. In: IEEE International Conference on Robotics and Biomimetics, pp. 1300–1305 (2013)Google Scholar
  13. 13.
    Pernkopf, F., Bouchaffra, D.: Genetic-based EM algorithm for learning Gaussian mixture models. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 1344–1348 (2005)CrossRefGoogle Scholar
  14. 14.
    Jin, G.Q., Li, W.D., Gao, L.: An adaptive process planning approach of rapid prototyping and manufacturing. Robotics and Computer-Integrated Manufacturing 29, 23–38 (2013)CrossRefGoogle Scholar
  15. 15.
    Gans, J., Shalloway, D.: Shadow mass and the relationship between velocity and momentum in symplectic numerical integration. Physical Review E 61, 4587–4592 (2000)CrossRefMathSciNetGoogle Scholar
  16. 16.
    Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital Image Processing Using MATLAB. Pearson Prentice Hall, New Jersey (2004)Google Scholar
  17. 17.
    Hiller, J., Lipson, H.: Automatic design and manufacture of soft robots. IEEE Transactions on Robotics 28(2), 457–466 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jürg Germann
    • 1
  • Joshua Auerbach
    • 1
  • Dario Floreano
    • 1
  1. 1.Laboratory of Intelligent Systems, EPFL - IMT - STI - LISLausanneSwitzerland

Personalised recommendations