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Abstract
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Article Information:
Fuzzy Neural Network based RFID Positioning and Navigation Method for Mobile Robots
Bo-Wen Hong, Ying-Jeh Huang, Chu-Yung Chen, Ping-Chou Wu and Wei-Chung Chen
Corresponding Author: Bo-Wen Hong
Submitted: October 30, 2012
Accepted: December 21, 2012
Published: July 05, 2013 |
Abstract:
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This study proposes the Radio Frequency Identification (RFID) indoor positioning and navigation method based on fuzzy neural network. The proposed method is applied to a wheelchair home health care robot with wireless communication. One reader and four tags are used. Based on the Received Signal Strength Indication (RSSI) data, the position of the robot can be determined. Further, to overcome the measurement error problem due to environmental parameter variation, a Fuzzy Neural Network (FNN) is proposed to compensate the measurement data. The FNN automatically adjust the weight, the variance and the mean value to overcome effectively the environmental parameter variation. A back-propagation algorithm is developed to achieve self-learning. The successful experiment results show that the proposed system architecture and positioning system provide satisfactory accuracy and make home health care wheelchair robot positioning system available for navigation and guidance.
Key words: Fuzzy neural network, indoor positioning, RFID, RSSI, wheelchair robot, ,
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Cite this Reference:
Bo-Wen Hong, Ying-Jeh Huang, Chu-Yung Chen, Ping-Chou Wu and Wei-Chung Chen, . Fuzzy Neural Network based RFID Positioning and Navigation Method for Mobile Robots. Research Journal of Applied Sciences, Engineering and Technology, (07): 1233-1239.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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