Visible Light Communication-based indoor localization using Gaussian Process
Kejie Qiu, Fangyi Zhang, Ming Liu
Abstract
For mobile robots and position-based services, such as healthcare service, precise localization is the most fundamental capability while low-cost localization solutions are with increasing need and potentially have a wide market. A low-cost localization solution based on a novel Visible Light Communication (VLC) system for indoor environments is proposed in this paper. A number of modulated LED lights are used as beacons to aid indoor localization additional to illumination. A Gaussian Process(GP) is used to model the intensity distributions of the light sources. A Bayesian localization framework is constructed using the results of the GP, leading to precise localization. Path-planning is hereby feasible by only using the GP variance field, rather than using a metric map. Dijkstra's algorithm-based path-planner is adopted to cope with the practical situations. We demonstrate our localization system by real-time experiments performed on a tablet PC in an indoor environment.
BibTeX
@inproceedings{iros2015_visiblelightcomm,
title = {Visible Light Communication-based indoor localization using Gaussian Process},
author = {Kejie Qiu and Fangyi Zhang and Ming Liu},
booktitle = {IROS 2015},
year = {2015}
}