Soft Autonomous Materials—Using Active Elasticity and Embedded Distributed Computation

  • Nikolaus CorrellEmail author
  • Çağdaş D. Önal
  • Haiyi Liang
  • Erik Schoenfeld
  • Daniela Rus
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 79)


The impressive agility of living systems seems to stem from modular sensing, actuation and communication capabilities, as well as intelligence embedded in the mechanics in the form of active compliance. As a step towards bridging the gap between man-made machines and their biological counterparts, we developed a class of soft mechanisms that can undergo shape change and locomotion under pneumatic actuation. Sensing, computation, communication and actuation are embedded in the material leading to an amorphous, soft material. Soft mechanisms are harder to control than stiff mechanisms as their kinematics are difficult to model and their degrees of freedom are large. Here we show instances of such mechanisms made from identical cellular elements and demonstrate shape changing, and autonomous, sensor-based locomotion using distributed control. We show that the flexible system is accurately modeled by an equivalent spring-mass model and that shape change of each element is linear with applied pressure. We also derive a distributed feedback control law that lets a belt-shaped robot made of flexible elements locomote and climb up inclinations. These mechanisms and algorithms may provide a basis for creating a new generation of biomimetic soft robots that can negotiate openings and manipulate objects with an unprecedented level of compliance and robustness.


Dielectric Elastomer Soft Mechanism Expansion Strain Soft Robot Active Elasticity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Abelson, H., Allen, D., Coore, D., Hanson, C., Homsy, G., Knight, T., Nagpal, R., Rauch, E., Sussman, G., Weiss, R.: Amorphous computing. Communications of the ACM 43(5), 74–82 (2000)CrossRefGoogle Scholar
  2. 2.
    Albu-Schaffer, A., Eiberger, O., Grebenstein, M., Haddadin, S., Ott, C., Wimbock, T., Wolf, S., Hirzinger, G.: Soft robotics. IEEE Robotics & Automation Magazine 15, 20–30 (2008)CrossRefGoogle Scholar
  3. 3.
    Bar-Cohen, Y.: Electroactive Polymer EAP Actuators as Artificial Muscles: Reality, potential and challenges, 2nd edn. SPIE Press (2004)Google Scholar
  4. 4.
    Brannon-Peppas, L., Peppas, N.: Dynamic and equilibrium swelling behaviour of ph-sensitive hydrogels containing 2-hydroxyethyl methacrylate. Biomaterials 11(9), 635–644 (1990)CrossRefGoogle Scholar
  5. 5.
    Camazine, S., Deneubourg, J.-L., Franks, N., Sneyd, J., Theraulaz, G., Bonabeau, E.: Self-Organization in Biological Systems. Princeton University Press (2003)Google Scholar
  6. 6.
    Chiechi, R.C., Weiss, E.A., Dickey, M.D., Whitesides, G.M.: Eutectic gallium-indium (egain): A moldable liquid metal for electrical characterization of self-assembled monolayers. Angewandte Chemie 47, 142–144 (2008)CrossRefGoogle Scholar
  7. 7.
    Clauset, A., Moore, C., Newman, M.E.J.: Hierarchical structure and the prediction of missing links in networks. Nature 453, 98–101 (2008)CrossRefGoogle Scholar
  8. 8.
    Fortuna, L., Frasca, M., Gioffre, M., La Rosa, M., Malagnino, N., Marcellino, A., Nicolosi, D., Occhipinti, L., Porro, F., Sicurella, G., Umana, E., Vecchione, R.: On the way to plastic computation. IEEE Circuits and Systems Magazine 8(3), 6–18 (2008)CrossRefGoogle Scholar
  9. 9.
    Hrozhyk, U., Serak, S., Tabiryan, N., White, T.J., Bunning, T.J.: Bidirectional photoresponse of surface pretreated azobenzene liquid crystal polymer networks. Optics Express 17, 716–722 (2009)CrossRefGoogle Scholar
  10. 10.
    Joseph, G., Czerniecki, J., Hannaford, B.: Mckibben artificial muscles: Pneumatic actuators with biomechanical intelligence. In: Proc. IEEE/ASME 1999 Intl. Conf. on Adv. Intell. Mechatronics, AIM (1999)Google Scholar
  11. 11.
    Linder, V., Gates, B.D., Ryan, D., Parviz, B.A., Whitesides, G.M.: Water-soluble sacrificial layers for surface micromachining. Small 1(7), 730–736 (2005)CrossRefGoogle Scholar
  12. 12.
    Lochmatter, T., Roduit, P., Cianci, C., Correll, N., Jacot, J., Martinoli, A.: Swistrack - a flexible open source tracking software for multi-agent systems. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, pp. 4004–4010 (2008)Google Scholar
  13. 13.
    Matsumoto, Y., Nakanishi, H., Hirai, S.: Rolling locomotion of a deformable soft robot with built-in power source. In: Proc. 11th Int. Conf. Climbing and Walking Robots and the Support Technologies for Mobile Machines (CLAWAR 2008), pp. 365–372 (September 2008)Google Scholar
  14. 14.
    McLeod, R.R., Kirchner, M.S., Kamysiak, K., Sullivan, A.C., Cole, M.: 3D waveguides with fiber couplers and 90 degree bends in holographic photopolymer. In: Proceedings of SPIE Organic 3D Photonics Materials and Devices V, San Diego, CA, vol. 6657 (September 2007)Google Scholar
  15. 15.
    Rus, D., Butler, Z., Kotay, K., Vona, M.: Self-reconfiguring robots. Communications of the ACM 45(3), 39–45 (2002)CrossRefGoogle Scholar
  16. 16.
    Scott, T.F., Kowalski, B.A., Sullivan, A.C., Bowman, C.N.: Two-color single-photon photoinitiation and photoinhibition for subdiffraction photolithography. Science (2009)Google Scholar
  17. 17.
    Seok, S., Onal, C.D., Wood, R., Rus, D., Kim, S.: Peristaltic locomotion with antagonistic actuators in soft robotics. In: Proceedings of IEEE International Conference on Robotics and Automation (2010) (in press)Google Scholar
  18. 18.
    Seung, H.S., Nelson, D.R.: Defects in flexible membranes with crystalline order. Physical Review A 38(2), 1005–1018 (1988)CrossRefGoogle Scholar
  19. 19.
    Steel, M.R., Harrison, F., Harper, P.G.: The piezoelectric bimorph: An experimental and theoretical study of its quasistatic response. Journal of Physics D: Applied Physics 11(6), 979–989 (1978)CrossRefGoogle Scholar
  20. 20.
    Sugiyama, Y., Hirai, S.: Crawling and jumping by a deformable robot. International Journal on Robotics Research 25(5–6), 603–620 (2006)CrossRefGoogle Scholar
  21. 21.
    Sullivan, A.C., Grabowski, M.W., McLeod, R.R.: Three-dimensional direct-write lithography into photopolymer. Applied Optics 46, 295–301 (2007)CrossRefGoogle Scholar
  22. 22.
    Todd, S., Xie, H.: An electrothermomechanical lumped element model of an electrothermal bimorph actuator. Journal of Microelectromechanical Systems 17(1), 213–225 (2008)CrossRefGoogle Scholar
  23. 23.
    Trivedi, D., Rahn, C., Kier, W., Walker, I.: Soft robotics: Biological inspiration, state of the art, and future research. Advanced Bionics and Biomechanics 5(2), 99–117 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2014

Authors and Affiliations

  • Nikolaus Correll
    • 1
    Email author
  • Çağdaş D. Önal
    • 2
  • Haiyi Liang
    • 3
  • Erik Schoenfeld
    • 4
  • Daniela Rus
    • 2
  1. 1.Department of Computer ScienceUniversity of Colorado at BoulderBoulderUSA
  2. 2.Computer Science and Artificial Intelligence LaboratoryMassachusetts Institute of TechnologyCambridgeUSA
  3. 3.School of Engineering and Applied SciencesHarvard UniversityCambridgeUSA
  4. 4.iRobot Inc.BedfordUSA

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