Canonical PSO based Nanorobot Control for Blood Vessel Repair

Authors: Pinfa Boonrong, Boonserm Kaewkamnerdpong

Abstract:

As nanotechnology advances, the use of nanotechnology for medical purposes in the field of nanomedicine seems more promising; the rise of nanorobots for medical diagnostics and treatments could be arriving in the near future. This study proposes a swarm intelligence based control mechanism for swarm nanorobots that operate as artificial platelets to search for wounds. The canonical particle swarm optimization algorithm is employed in this study. A simulation in the circulatory system is constructed and used for demonstrating the movement of nanorobots with essential characteristics to examine the performance of proposed control mechanism. The effects of three nanorobot capabilities including their perception range, maximum velocity and respond time are investigated. The results show that canonical particle swarm optimization can be used to control the early version nanorobots with simple behaviors and actions.

Keywords: Artificial platelets, canonical particle swarm optimization, nanomedicine, nanorobot, swarm intelligence.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328488

References:

[1] R. P. Feynman, "There's Plenty of Room at the Bottom: An Invitation to Enter a New Field of Physics," Engineering and Science, vol. 23, 1960.
[2] The National Nanotechnology Initiative (NNI). (2011, 04 Mar). Nanotechnology Big Things from a Tiny World. Available: http://www.nano.gov/Nanotechnology_BigThingsfromaTinyWorldsprea d.pdf
[3] E. K. Drexler, Engines of Creation 2.0 : The Coming Era of Nanotechnology, 20th anniversary ed., 2006.
[4] A. F. J. Robert, "Exploratory design in medical nanotechnology: A mechanical artificial red cell, " Artificial Cells, Blood Substitutes, and Immobilization Biotechnology, vol. 26, pp. 411-430, 1998.
[5] A. F. J. Robert, "Microbivores: Artificial Mechanical Phagocytes using Digest and Discharge Protocol," Journal of Evolution and Technology, vol. 14, pp. 1-52, 2005.
[6] A. F. J. Robert. (2011, 26 May). Clottocytes: Artificial Mechanical Platelets. Foresight Update 41. Available: http://www.imm.org/publications/reports/rep018/
[7] A. F. J. Robert and A. Cavalcanti, "A Norobotics Control Design: A Collective Behavior Approach for Medicine," IEEE Transactions on Nanobioscience, vol. 4, pp. 133-140, 2005.
[8] B. Kaewkamnerdpong and P. J. Bentley, "Computer science for nanotechnology: Needs and opportunities," in Proc. 5th International Conference on Intelligent Processing and Manufacturing of Materials, California, 2005.
[9] D. S. Goodsell, Bionanotechnology: Lesson from Nature. Canada: Wiley-Liss, 2004.
[10] E. Bonabeau, et al., Swarm Intelligence: From Natural To Artificial Systems. New York: Oxford University Press, 1999.
[11] A. P. Engelbrecht, Computational Intelligence: An Introduction: John Wiley & Sons, 2007.
[12] G. J. Tortora and B. H. Derrickson, Principles of Anatomy and Physiology: Maintenance and continuity of the human body, 12th, Ed.: John Wiley & Sons, 2009.
[13] I. I. Salles, H.B. Feys, B.F. Iserbyt, S.F. De Meyer , K. Vanhoorelbeke and H. Deckmy, "Inherited traits affecting platelet function," Blood Reviews vol. 22, pp. 155-172, 2008.
[14] M. Franchini, G. Lippi, D. Veneri, G. Targher, M. Zaffanello and G.C. Guidi, "Inherited platelet disorders," Clinica Chimica Acta, vol. 387, pp. 1-8, 2008.
[15] A. ColorniM, Dorigo, V. Maniezzo, D. Elettronica and P. Milano, "Distributed Optimization by Ant Colonies," in Proc. 1st European Conference on Artificial Life, 1992, pp. 134-142.
[16] M. Dorigo and L. Gambardella, "Ant colony system: a cooperative learning approach to the traveling salesman problem," IEEE Transactions on Evolutionary Computation, vol. 1, pp. 53-66, 1997.
[17] D. Payton and M. Daily, "Pheromone robotics," Autonomous Robots, vol. 11, pp. 319-324, 2001.
[18] D. Karaboga and B. Basturk, "A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm," Journal of Global Optimization, vol. 39, 2007.
[19] R. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Proc. 6th International Symposium on Micro Machine and Human Science, Nagoya, Japan, 1995, pp. 39-43.
[20] B. Kaewkamnerdpong and P. J. Bentley, "Modelling Nanorobot Control using Swarm Intelligence : A Pilot Study," in Innovations in Swarm Intelligence, ed: Springer, 2009, pp. 175-214.
[21] M. Clerc and J. Kennedy, "The particle swarm - explosion, stability, and convergence in a multidimensional complex space," IEEE Transactions on Evolutionary Computation, vol. 6, pp. 58-73, 2002.
[22] W. F. Ganong, Review of Medical Physiology: McGraw-Hill, 2005.
[23] A. M. K. Dagamseh, T.S.J. Lammerink, M.L. Kolster and R. J. Bruinink, "Dipole-source localization using biomimetic flow-sensor arrays positioned as lateral-line system," Sensors and Actuators A: Physical, vol. 162, 2010.