Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Murata, S., Kurokawa, H.: Self-Organizing Robots. Springer Tracts in Advanced Robotics, vol. 77 (2012)
Whitesides, G.M., Grzybowski, B.: Self-assembly at all scales. Science 295, 2418–2421 (2002)
Pelesko, J.A.: Self assembly: the science of things that put themselves together. CRC Press (2007)
Gross, R., Dorigo, M.: Self-Assembly at the Macroscopic Scale. Proceedings of the IEEE 96, 1490–1508 (2008)
Pfeifer, R., Lungarella, M., Iida, F.: Self-Organization, Embodiment, and Biologically Inspired Robotics. Science 318, 1088–1093 (2007)
Griffith, S.: Growing Machines. PhD Thesis. MIT (2004)
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)
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)
Yim, S., Sitti, M.: SoftCubes: Towards a Soft Modular Matter. In: IEEE International Conference on Robotics and Automation, pp. 530–536 (2013)
Risi, S., Cellucci, D., Lipson, H.: Ribosomal Robots: Evolved Designs Inspired by Protein Folding. In: GECCO 2013, pp. 263–270 (2013)
Germann, J., Maesani, A., Pericet-Camara, R., Floreano, D.: Soft Cells for Programmable Self-Assembly of Robotic Modules (Under review)
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)
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)
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)
Gans, J., Shalloway, D.: Shadow mass and the relationship between velocity and momentum in symplectic numerical integration. Physical Review E 61, 4587–4592 (2000)
Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital Image Processing Using MATLAB. Pearson Prentice Hall, New Jersey (2004)
Hiller, J., Lipson, H.: Automatic design and manufacture of soft robots. IEEE Transactions on Robotics 28(2), 457–466 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Germann, J., Auerbach, J., Floreano, D. (2014). Programmable Self-assembly with Chained Soft Cells: An Algorithm to Fold into 2-D Shapes. In: del Pobil, A.P., Chinellato, E., Martinez-Martin, E., Hallam, J., Cervera, E., Morales, A. (eds) From Animals to Animats 13. SAB 2014. Lecture Notes in Computer Science(), vol 8575. Springer, Cham. https://doi.org/10.1007/978-3-319-08864-8_21
Download citation
DOI: https://doi.org/10.1007/978-3-319-08864-8_21
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08863-1
Online ISBN: 978-3-319-08864-8
eBook Packages: Computer ScienceComputer Science (R0)