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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic


eISSN: 1178-5608



VOLUME 1 , ISSUE 3 (September 2008) > List of articles


Ahmed M. Elmogy / Fakhreddine O. Karray

Keywords : Mobile sensors, target tracking, Kohonen neural network, clustering

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 1, Issue 3, Pages 716-734, DOI:

License : (CC BY-NC-ND 4.0)

Published Online: 13-December-2017



Sensors provide a key feedback link allowing robotic and autonomous systems to react to their environments. Without this feedback, robotic and autonomous systems will operate in an uncontrolled manner, since they don’t have the ability to perceive and respond to their environments. The limited capabilities of static sensors especially in complex applications and environments force the use of multiple sensors operating dynamically. This paper addresses the development of multiple objects tracking system using multiple mobile sensors. For the purposes of surveillance and security, trackers use an Extended Kohonen neural network to track the moving targets in their environments. The proposed tracking algorithm can be used for single and multiple target tracking. A clustering algorithm is used in order to minimize the number of active trackers over time and hence save energy. An auction based algorithm
is used for the purpose of optimizing the cooperation between trackers. Quantitative and qualitative comparisons with other recent multi target tracking approaches show that our proposed tracking algorithm can provide a good coverage, and a better energy saving.

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[1] B. P. Gerkey, and M. J. Mataric, ” Sold!: Auction Methods for Multirobot Coordination”, IEEE Transactions on Robotics and Automation, Vol. 18, No. 5,pp. 785-768, Oct. 2002.
[2] J. O’Rourke,” Art Gallery Theorems and Algorithms”, London, U.K.: Oxford Univ. Press, 1987.
[3] K. Hsiang, W. Leow, and M. Ang,” Autonomic Mobile Sensor Network With Self- Coordinated Task Allocation and Execution”, IEEE Trans. On SMC- Part C, Vol. 36, No. 3, pp. 315-327, May 2006.
[4] N. Heo, and P. Varsheny,” Energy Efficient Deployment of Intelligent Mobile sensor Networks”, IEEE Transactions on SMC- Part A, Vol. 35, No. 1, pp. 78-92,Jan. 2005.
[5] H. Qi, S. S. Iyengar, and K. Chakrabarty,” Distributed sensor fusion-a review of recent research”, J. Franklin Inst., Vol. 338, pp 655-668, 2001.
[6] A. Howard, M. J. Mataric, and G. S. Sukhatme,” Mobile sensor network deployment using potential fields: A distributed, scalable solution to the area coverage problem”, in Proc. 6th Int. Conf. Distributed Autonomous Robotic Systems, Fukuoka, Japan, pp 299-308, 2002.
[7] J. Cortes, S. Mart´ınez, T. Karatas, and F. Bullo,” Coverage Control for Mobile Sensing Networks”, IEEE Transactions On Robotics and Automation, Vol. 20, No. 2, pp. 243-255, April 2004.
[8] Y. B. Shalom, and T. E. Fortmann,” Tracking and data Association”, Academic Press, Inc., Orlando, Florida, 1988.
[9] P. L. Bogler,” Radar principles with applications to tracking systems”, John Wiley & Sons, New York 1990
[10] F. Gustafsson, F. Gunnarsson, K. Bergman, U. Forssell, J. Jansson, R.Karlsson, and P. J. Nordlund,” Particle filters for positioning, navigation, and tracking”, IEEE Transactions on Signal Processing, Vol. 50, No. 2, pp 425-437,Feb. 2002.
[11] M. Isard, and A. Blake,” Condensation- conditional propagation for visual tracking”, International Journal of Computer Vision, Vol. 29, No. 1, pp 5-28,1998.
[12] D. Liu and L. C. Fu,” Target tracking in an environment of nearly stationary and biased clutter”, In Proceedings of the 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 1358- 1363, Maui, Hawaii, Oct.2001.
[13] W. Zhang, and G. Cao,” Optimizing free reconfiguration for mobile target tracking in sensor network”, In Proceedings of the IEEE International Conference on Computer Communication, pp. 2434-2445, March 2004.
[14] R. Murrieta, H. G. Banos, and B. Tavar,” A reactive motion planner to maintain visibility of unpredictable targets”, In Proceedings of IEEE International Conference on Robotics and Automation, pp 4242-4247, Washington DC, May 2002.
[15] L. E. Parker,” Distributed algorithms for multi-robot observation of multiple moving targets”, International Journal of Autonomous Robots, Vol. 12, No. 3,pp 231-255, 2002.
[16] L. E. Parker,” Cooperative robotics for multi-target Observation”, Intelligent Automation and Soft Computing, special issue on Robotics Research at Oak Ridge National Laboratory, Vol. 5, No. 1, pp 5-19, 1999.
[17] A. Kolling and S. Carpin,” Multi-robot cooperation for surveillance of multiple moving targets - a new behavioral approach”, In Proceedings of the IEEE International Conference on Robotics and automation, pp 1311-1316, 2006.
[18] A. Kolling, and S. Carpin,” Cooperative observation of multiple moving targets: an algorithm and its formalization”, International Journal of Robotics Research, Vol. 26, No. 9, pp 935-953 , Nov. 2007.
[19] B. Jung, and G. S. Sukhatme,” Tracking targets using multiple robots: The effect of environment occlusion”, Autonomous Robots, Vol. 13, No. 3, pp 191-205, 2002.
[20] T. Kanungo, D. M. Mount,N. S. Netanyahu, C. D. Piatko, R. Silverman, and A. Y. Wu,” An Efficient k-Means Clustering Algorithm: Analysis and Implementation”, IEEE Transactions on Pattern Analysis and Machine Intelligence,Vol. 24, No. 7, pp. 881-891, July 2002.
[21] L. M. Gambardella, C. Versino”, Learning The Visuomotor Coordination Of A Mobile Robot By Using The Invertible Kohonen Map”, From Natural to Artificial Neural Computation, International Workshop on Artificial Neural Networks Proceedings, pp. 1084-1091, Berlin, 1995.
[22] T. Kohonen,” Self-Organization and Associative Memory”, Springer Series in Information Sciences,Vol. 8, Berlin, 1988.
[23] G. R. Mir,” Mobot simulator”,