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JRM Vol.23 No.4 pp. 475-483
doi: 10.20965/jrm.2011.p0475
(2011)

Paper:

Probabilistic Localization of Mobile Wireless LAN Client in Multistory Building Based on Sparse Bayesian Learning

Tomohiro Umetani*, Tomoya Yamashita**, and Yuichi Tamura*

*Department of Intelligence and Informatics, Konan University, 8-9-1 Okamoto, Higashinada, Kobe, Hyogo 658-8501, Japan

**Graduate School of Natural Science, Konan University

Received:
January 11, 2011
Accepted:
April 27, 2011
Published:
August 20, 2011
Keywords:
localization, wireless LAN, multistory building, probabilistic model, sparse Bayesian learning
Abstract

This paper describes a method for localizing wireless mobile clients in a multistory building using a public wireless Local Area Network (LAN) system. Physical location data on personal devices and mobile robots is important to information services and robot applications. Wireless mobile clients are localized in a multistory building using public wireless LAN access points placed, three-dimensionally in the building. Information on the floor number and client location is acquired probabilistically, with estimation providing a probabilistic model for localization based on sparse Bayesian learning. Results of experiments confirm the feasibility of our proposal.

Cite this article as:
Tomohiro Umetani, Tomoya Yamashita, and Yuichi Tamura, “Probabilistic Localization of Mobile Wireless LAN Client in Multistory Building Based on Sparse Bayesian Learning,” J. Robot. Mechatron., Vol.23, No.4, pp. 475-483, 2011.
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