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JRM Vol.35 No.3 pp. 780-787
doi: 10.20965/jrm.2023.p0780
(2023)

Paper:

Indoor Positioning Scheme Using Off-the-Shelf Lighting Fixtures’ Fingerprints

Hiroyuki Kobayashi

Osaka Institute of Technology
1-45 Chayamachi, Kita-ku, Osaka, Osaka 530-8568, Japan

Received:
November 28, 2022
Accepted:
February 28, 2023
Published:
June 20, 2023
Keywords:
CEPHEID, self localization, indoor positioning, deep neural network, environmental fingerprint
Abstract

This paper discusses an indoor positioning technique aimed at human-centric services such as pedestrian navigation or service robots. The method is called “CEPHEID” and uses a light flickering pattern as an environmental fingerprint. The authors found that each lighting fixture has unique and distinguishable flickering characteristics. In this paper, CEPHEID is introduced as a “classifier” and its validity is shown based on experimental results. Additionally, an approach for improving the positional precision is proposed. The classifier and regressor are combined to create a zone-classified regressor model for CEPHEID. The basic performance of this concept is also tested using an experiment.

The positioning using flickering fingerprints

The positioning using flickering fingerprints

Cite this article as:
H. Kobayashi, “Indoor Positioning Scheme Using Off-the-Shelf Lighting Fixtures’ Fingerprints,” J. Robot. Mechatron., Vol.35 No.3, pp. 780-787, 2023.
Data files:
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