Distributed Intelligent MEMS: Progresses and Perspectives

Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 150)


MEMS research has until recently focused mainly on the engineering process, resulting in interesting products and a growing market. To fully realize the promise of MEMS, the next step is to add embedded intelligence. With embedded intelligence, the scalability of manufacturing will enable distributed MEMS systems consisting of thousands or millions of units which can work together to achieve a common goal. However, before such systems can become a reallity, we must come to grips with the challenge of scalability which will require paradigm-shifts both in hardware and software. Furthermore, the need for coordinated actuation, programming, communication and mobility management raises new challenges in both control and programming. The objective of this article is to report the progresses made by taking the example of two research projects and by giving the remaining challenges and the perspectives of distributed intelligent MEMS.


Wireless Sensor Network Mobility Management Logical Topology Modular Robot Spherical Robot 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Andersen, D.G., Balakrishnan, H., Kaashoek, M.F., Morris, R.: Resilient Overlay Networks. In: Proc. 18th ACM Symposium on Operating Systems Principles (SOSP), Banff, Canada, pp. 131–145 (2001)Google Scholar
  2. 2.
    Ashley-Rollman, M.P., De Rosa, M., Srinivasa, S.S., Pillai, P., Goldstein, S.C., Campbell, J.D.: Declarative programming for modular robots. In: Workshop on Self-Reconfigurable Robots/Systems and Applications, IROS 2007 (2007), http://www.cs.cmu.edu/claytronics/papers/ashley-rollman-derosa-iros07wksp.pdf
  3. 3.
    Ashley-Rollman, M.P., Goldstein, S.C., Lee, P., Mowry, T.C., Pillai, P.: Meld: A declarative approach to programming ensembles. In: Proceedings of the IEEE International Conference on Intelligent Robots and Systems, IROS 2007 (2007), http://www.cs.cmu.edu/~claytronics/papers/ashley-rollman-iros07.pdf
  4. 4.
    Ashley-Rollman, M.P., Lee, P., Goldstein, S.C., Pillai, P., Campbell, J.D.: A Language for Large Ensembles of Independently Executing Nodes. In: Hill, P.M., Warren, D.S. (eds.) ICLP 2009. LNCS, vol. 5649, pp. 265–280. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  5. 5.
    Ashton, K.: That ’internet of things’ thing. RFID Journal (2009)Google Scholar
  6. 6.
    Baz, D.E., Boyer, V., Bourgeois, J., Dedu, E., Boutoustous, K.: Distributed part differentiation in a smart surface. Mechatronics (2011)Google Scholar
  7. 7.
    Berlin, A., Gabriel, K.: Distributed mems: New challenges for computation. IEEE Computational Science and Engineering Journal 4(1), 12–16 (1997)CrossRefGoogle Scholar
  8. 8.
    Boutoustous, K., Dedu, E., Bourgeois, J.: An exhaustive comparison framework for distributed shape differentiation in a MEMS sensor actuator array. In: International Symposium on Parallel and Distributed Computing (ISPDC), pp. 429–433. IEEE computer society press, Krakow (2008)Google Scholar
  9. 9.
    Boutoustous, K., Laurent, G.J., Dedu, E., Matignon, L., Bourgeois, J., Fort-Piat, N.L.: Distributed control architecture for smart surfaces. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2018–2024. IEEE, Taipei (2010)Google Scholar
  10. 10.
    Chapuis, Y.-A., Zhou, L., Casner, D., Ai, H., Hervé, Y.: FPGA-in-the-loop for control emulation of distributed MEMS simulation using VHDL-AMS. In: Proc. of the 1st Workshop on Hardware and Software Implementation and Control of Distributed MEMS (dMEMS2010), pp. 92–99. IEEE CPS (2010)Google Scholar
  11. 11.
    De Rosa, M., Goldstein, S.C., Lee, P., Campbell, J.D., Pillai, P.: Programming modular robots with locally distributed predicates. In: Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2008 (2008)Google Scholar
  12. 12.
    De Rosa, M., Goldstein, S.C., Lee, P., Campbell, J.D., Pillai, P.: Programming modular robots with locally distributed predicates. In: Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2008 (2008), http://www.cs.cmu.edu/~claytronics/papers/derosa-icra08.pdf
  13. 13.
    Dedu, E., Bourgeois, J., Boutoustous, K.: Simulation to help calibration of a mems sensor network. International Journal of Pervasive Computing and Communications 6(4) (2010)Google Scholar
  14. 14.
    Derbakova, A., Correll, N., Rus, D.: Decentralized self-repair to maintain connectivity and coverage in networked multi-robot systems. In: Proc. of IEEE International Conference on Robotics and Automation, ICRA (2011)Google Scholar
  15. 15.
    Ghosh, S., Bayoumi, M.: On integrated cmos-mems system-on-chip. In: The 3rd International IEEE-NEWCAS Conference, pp. 31–34 (2005)Google Scholar
  16. 16.
    Giorgetti, A., Hammad, A., Tatibouët, B.: Using SysML for smart surface modeling. In: dMEMS 2010, 1st Workshop on Design, Control and Software Implementation for Distributed MEMS, pp. 100–107. IEEE Computer Society Press, Besançon (2010)CrossRefGoogle Scholar
  17. 17.
    Goldstein, S.C., Mowry, T.C., Campbell, J.D., Ashley-Rollman, M.P., De Rosa, M., Funiak, S., Hoburg, J.F., Karagozler, M.E., Kirby, B., Lee, P., Pillai, P., Reid, J.R., Stancil, D.D., Weller, M.P.: Beyond audio and video: Using claytronics to enable pario. AI Magazine 30(2) (2009)Google Scholar
  18. 18.
    Gro, R., Bonani, M., Mondada, F., Dorigo, M.: Autonomous self-assembly in swarm-bots. IEEE Transactions on Robotics 22(6), 1115–1130 (2006)Google Scholar
  19. 19.
    Hornbeck, L.J.: Digital Light Processing for high-brightness high-resolution applications. In: Wu, M.H. (ed.) Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series. Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, vol. 3013, pp. 27–40 (1997)Google Scholar
  20. 20.
    Karagozler, M.E., Thaker, A., Goldstein, S.C., Ricketts, D.S.: Electrostatic actuation and control of micro robots using a post-processed high-voltage soi cmos chip. In: IEEE International Symposium on Circuits and Systems, ISCAS (2011)Google Scholar
  21. 21.
    Matignon, L., Laurent, G.J., Le Fort-Piat, N., Chapuis, Y.A.: Designing decentralized controllers for distributed-air-jet mems-based micromanipulators by reinforcement learning. Journal of Intelligent and Robotic Systems 145(2), 59–80 (2010)MATHGoogle Scholar
  22. 22.
    Lee, E.A.: Cyber physical systems: Design challenges. In: IEEE International Symposium on Object-Oriented Real-Time Distributed Computing, vol. 0, pp. 363–369 (2008)Google Scholar
  23. 23.
    Lewis, A., Bekey, G.: The behavioral self-organization of nanorobots using local rules. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (1992)Google Scholar
  24. 24.
    Reid, J.R., Vasilyev, V.S., Webster, R.T.: Building micro-robots: A path to sub-mm3 autonomous systems. In: Proceedings of Nanotech. (2008)Google Scholar
  25. 25.
    Rister, B.D., Campbell, J., Pillai, P., Mowry, T.C.: Integrated debugging of large modular robot ensembles. In: ICRA, pp. 2227–2234 (2007)Google Scholar
  26. 26.
    Royer, E., Toh, C.K.: A review of current routing protocols for ad hoc mobile wireless networks. IEEE Personal Communications 6(2), 46–55 (1999)CrossRefGoogle Scholar
  27. 27.
    Schwager, M., Slotine, J.J., Rus, D.: Decentralized, adaptive control for coverage with networked robots. In: 2007 IEEE International Conference on Robotics and Automation, pp. 3289–3294 (2007)Google Scholar
  28. 28.
    Vasilyev, V.S., Reid, J.R., Webster, R.T.: Microfabrication of si/sio2-spherical shells as a path to sub-mm3 autonomous robotic systems. In: MRS Fall Meeting (2008)Google Scholar
  29. 29.
    Wang, Y.: Topology control for wireless sensor networks. In: Li, Y., Thai, M.T., Wu, W. (eds.) Wireless Sensor Networks and Applications, Signals and Communication Technology, pp. 113–147. Springer, US (2008)CrossRefGoogle Scholar
  30. 30.
    Witvrouw, A.: Cmos-mems integration: why, how and what? In: Proceedings of the 2006 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2006, pp. 826–827. ACM (2006)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.University of Franche-ComtéMontbeliardFrance
  2. 2.Carnegie Mellon UniversityPittsburghUSA

Personalised recommendations