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http://dx.doi.org/10.7472/jksii.2013.14.6.09

Design and Implementation of RSSI-based Intelligent Location Estimation System  

Lim, Chang Gyoon (Computer Engineering, Chonnam National Univ.)
Kang, O Seong Andrew (Computer Engineering, Chonnam National Univ.)
Lee, Chang Young (Computer Engineering, Chonnam National Univ.)
Kim, Kang Chul (Computer Engineering, Chonnam National Univ.)
Publication Information
Journal of Internet Computing and Services / v.14, no.6, 2013 , pp. 9-18 More about this Journal
Abstract
In this paper, we design and implement an intelligent system for finding objects with RFID(Radio Frequency IDentification) tag in which an mobile robot can do. The system we developed is a learning system of artificial neural network that uses RSSI(Received Signal Strength Indicator) value as input and absolute coordination value as target. Although a passive RFID is used for location estimation, we consider an active RFID for expansion of recognition distance. We design the proposed system and construct the environment for indoor location estimation. The designed system is implemented with software and the result related learning is shown at test bed. We show various experiment results with similar environment of real one from earning data generation to real time location estimation. The accuracy of location estimation is verified by simulating the proposed method with allowable error. We prepare local test bed for indoor experiments and build a mobile robot that can find the objects user want.
Keywords
RSSI; location estimation; artificial neural network; mobile robot; RFID;
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  • Reference
1 Komoriya, K., Oyama., "Position Esitimation of a Mobile Robot using Optical Fiber Gyroscope," in Proc. IEEE/RSJ/CI International Conference on Intelligent Robots and Systems IROS '94, vol. 1, pp. 143-149, 12-16, Sep. 1994
2 Kulyukin, V., Gharpure, C., Nicholson, J., Pavithran, S., "RFID in Robot-assisted Indoor Navigation for the Visually Impaired," in Proc. IEEE/RSJ/CI International Conference on Intelligent Robots and Systems IROS '2004, vol. 2, pp. 1979-1984, Sep. 2004
3 Luis Bras, Nuno Borges Carvalho, Pedro Pinho, Lukasz Kulas, and Krzysztof Nyka "A Review of Antennas for Indoor Positioning Systems," International Journal of Antennas and Propagation Volume 2012, Article ID 953269, 2012
4 J. Blumenthal, R. Grossmann, F. Golatowski, and D. Timmermann (2007) "Weighted Centroid Localization in Zigbee-based Sensor Networks." Intelligent Signal Processing. WISP 2007. IEEE International Symposium on, pp. 1-6.
5 F. Rosenblatt, Principles of neurodynamics: perceptron and the theory of brain mechanisms. Spartan, New York, 1962
6 M. Minsky and S. Papert, Perceptrons, MIT Press, Cambridge, MA, 1969
7 R. O. Duda, P. E. Hart, and D. G. Strok, Pattern Classification, New York, Wiley, 2001
8 S. Shigetoshi, F. Toshio, and S. Takanori, A Neural Network Architecture for Incremental Learning, Neorocomputing, 9, pp.111-130, 1995   DOI   ScienceOn
9 J. S. Jang, C. T. Sun and E. Mizutani, Neurofuzzy and Soft Computing, USA, Prentice Hall, 1997