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Sensors 2015, 15(3), 5311-5330;

Fast Fingerprint Database Maintenance for Indoor Positioning Based on UGV SLAM

GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430000, China
Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, Geodeetinrinne 2, Kirkkonummi FI-02431, Finland
Department of Navigation and Positioning, Finnish Geospatial Research Institute, Geodeetinrine 2, Kirkkonummi FI-02431, Finland
Department of Real Estate, Planning and Geoinformatics, Aalto University, P.O. Box 11000, Espoo FI-00076, Finland
Conrad Blucher Institute of Surveying & Science, Texas A&M University at Corpus Christi, Corpus Christi, TX 77843-3577, USA
Author to whom correspondence should be addressed.
Academic Editors: Kourosh Khoshelham and Sisi Zlatanova
Received: 13 November 2014 / Revised: 16 February 2015 / Accepted: 17 February 2015 / Published: 4 March 2015
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
Full-Text   |   PDF [4549 KB, uploaded 4 March 2015]   |  


Indoor positioning technology has become more and more important in the last two decades. Utilizing Received Signal Strength Indicator (RSSI) fingerprints of Signals of OPportunity (SOP) is a promising alternative navigation solution. However, as the RSSIs vary during operation due to their physical nature and are easily affected by the environmental change, one challenge of the indoor fingerprinting method is maintaining the RSSI fingerprint database in a timely and effective manner. In this paper, a solution for rapidly updating the fingerprint database is presented, based on a self-developed Unmanned Ground Vehicles (UGV) platform NAVIS. Several SOP sensors were installed on NAVIS for collecting indoor fingerprint information, including a digital compass collecting magnetic field intensity, a light sensor collecting light intensity, and a smartphone which collects the access point number and RSSIs of the pre-installed WiFi network. The NAVIS platform generates a map of the indoor environment and collects the SOPs during processing of the mapping, and then the SOP fingerprint database is interpolated and updated in real time. Field tests were carried out to evaluate the effectiveness and efficiency of the proposed method. The results showed that the fingerprint databases can be quickly created and updated with a higher sampling frequency (5Hz) and denser reference points compared with traditional methods, and the indoor map can be generated without prior information. Moreover, environmental changes could also be detected quickly for fingerprint indoor positioning. View Full-Text
Keywords: laser scanning; fingerprint database; indoor positioning; SLAM; SOP laser scanning; fingerprint database; indoor positioning; SLAM; SOP

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Tang, J.; Chen, Y.; Chen, L.; Liu, J.; Hyyppä, J.; Kukko, A.; Kaartinen, H.; Hyyppä, H.; Chen, R. Fast Fingerprint Database Maintenance for Indoor Positioning Based on UGV SLAM. Sensors 2015, 15, 5311-5330.

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