Advertisement

Early-Stage Diagnosis of Endogenous Diseases by Swarms of Nanobots: An Applicative Scenario

  • Paolo Amato
  • Massimo Masserini
  • Giancarlo Mauri
  • Gianfranco Cerofolini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6234)

Abstract

The development of artificial devices (nanobots), working as blood white cells but addressed to the recognition and eventually the destruction of endogenous pathological states, is an ambitious goal. Swarm intelligence can be a key element to successfully tackle the challenges posed by this goal. Here we describe an applicative scenario, based on swarm of nanobots, by sketching the environment in which the nanobots operate, the constraints related to their physical implementation, and the tasks they have to tackle. In this scenario, we propose to use collisions between nanorobots as a way of communication inside the swarm.

Keywords

Swarm Intelligence Nanorobotics Nanotechnology  Fractals Medicine 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm intelligence: from natural to artificial systems. Oxford University Press, Inc., New York (1999)Google Scholar
  2. 2.
    Brooks, R.: New approaches to robotics. Science 253, 1227–1232 (1991)CrossRefGoogle Scholar
  3. 3.
    Cavalcanti, A., Hogg, T., Shirinzadeh, B., Liaw, H.: Nanorobot communication techniques: A comprehensive tutorial. In: ICARCV, pp. 1–6. IEEE, Los Alamitos (2006)Google Scholar
  4. 4.
    Cerofolini, G.F.: Two routes to subcellular sensing. In: Korkin, A., Krstic, P., Wells, J. (eds.) Nano and Giga Challenges in Electronics, Photonics and Renewable Energy (NGC 2009). Springer, Berlin (2010) (to be published)Google Scholar
  5. 5.
    Cerofolini, G.F., Amato, P.: Swarms of nanobots for in vivo diagnosis of endogenous diseases (2010), http://asdn.net/asdn/life/nanorobots2.shtml
  6. 6.
    Cerofolini, G.F., Amato, P., Masserini, M., Mauri, G.: A surveillance system for early-stage diagnosis of endogenous diseases by swarms of nanobots. Advanced Science Letters 3 (2010) (to be published)Google Scholar
  7. 7.
    Freitas, R.: Pharmacytes: An ideal vehicle for targeted drug delivery. Journal of Nanoscience and Nanotechnology 6, 2769–2775 (2006)CrossRefGoogle Scholar
  8. 8.
    Gabrys, E., Rybaczuk, M., Kedzia, A.: Fractal models of circulatory system. Symmetrical and asymmetrical approach comparison. Chaos, Solitons & Fractals 24(3), 707–715 (2005)zbMATHGoogle Scholar
  9. 9.
    Lee, S., Ferrari, M., Decuzzi, P.: Shaping nano-/micro-particles for enhanced vascular interaction in laminar flows. Nanotechnology 20, 495101 (2009)CrossRefGoogle Scholar
  10. 10.
    Mandelbrot, B.B.: The Fractal Geometry of Nature. W. H. Freedman and Co., New York (1983)Google Scholar
  11. 11.
    Martel, S., Mohammadi, M.: Using a swarm of self-propelled natural microrobots in the form of flagellated bacteria to perform complex micro-assembly tasks. In: Proc. of the 2010 IEEE Int. Conf. on Robotics and Automation (ICRA). IEEE, Los Alamitos (2010)Google Scholar
  12. 12.
    Murray, C.D.: The physiological principle of minimum work applied to the angle of branching of arteries. J. Gen. Physiol. 9(6), 835–841 (1926)CrossRefGoogle Scholar
  13. 13.
    Nagy, Z., Harada, K., Flückiger, M., Susilo, E., Kaliakatsos, I.K., Menciassi, A., Hawkes, E., Abbott, J.J., Dario, P., Nelson, B.J.: Assembling reconfigurable endoluminal surgical systems: Opportunities and challenges. International Journal of Biomechatronics and Biomedical Robotics 1(1), 3–16 (2009)CrossRefGoogle Scholar
  14. 14.
    Requicha, A.A.G.: Nanorobots, NEMS, and nanoassembly. Proceedings of the IEEE 91(11), 1922–1933 (2003)CrossRefGoogle Scholar
  15. 15.
    Roncucci, P., Pirondini, L., Paderni, G., Massera, C., Dalcanale, E., Azov, V., Diederich, F.: Conformational behavior of pyrazine-bridged and mixed-bridged cavitands: A general model for solvent effects on thermal vase-kite switching. Chem. Eur. J. 12, 4775–4784 (2006)CrossRefGoogle Scholar
  16. 16.
    Service, R.F.: Nanotechnology takes aim at cancer. Science 310(5751), 1132–1134 (2005)CrossRefGoogle Scholar
  17. 17.
    Winfield, A.F.T.: Distributed sensing and data collection via broken ad hoc wireless connected networks of mobile robots. In: Parker, L.E., Bekey, G.A., Barhen, J. (eds.) DARS, pp. 273–282. Springer, Heidelberg (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Paolo Amato
    • 1
  • Massimo Masserini
    • 2
  • Giancarlo Mauri
    • 1
  • Gianfranco Cerofolini
    • 3
  1. 1.DISCoUniversity of Milano–BicoccaMilanoItaly
  2. 2.Department of Experimental MedicineUniversity of Milano–BicoccaMilanoItaly
  3. 3.CNISM and Department of Materials ScienceUniversity of Milano–BicoccaMilanoItaly

Personalised recommendations