Chang Gyoon Lim, O Seong Andrew Kang, Chang Young Lee, Kang Chul Kim, Journal of Internet Computing and Services, Vol. 14, No. 6, pp. 9-18, Dec. 2013
10.7472/jksii.2013.14.6.09, Full Text:  HTML
Keywords: RSSI, location estimation, Artificial neural network, mobile robot, RFID

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.

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