VLC-Based Indoor Localization

Dec 31, 2014

This is a project I worked on with Prof. Ming Liu and Mr. Kejie Qiu when I was a research assistant in the RAM-LAB at HKUST.

Contributions:

Developed a beacon code selection algorithm and a decomposition algorithm for blindly mixed beacon signals, based on CDMA code selection principles and Gold-sequence correlation properties (Zhang et al., 2015).
Participated in the development of a light intensity distribution map generation algorithm using Gaussian Process Regression (Qiu et al., 2015).
Participated in the development of localization and path planning algorithms using Kalman Filter (KF) and A star (Qiu et al., 2015).

References

2015

Asynchronous blind signal decomposition using tiny-length code for visible light communication-based indoor localization

Fangyi Zhang, Kejie Qiu, and Ming Liu

In IEEE International Conference on Robotics and Automation (ICRA), Dec 2015

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Indoor localization is a fundamental capability for service robots and indoor applications on mobile devices. To realize that, the cost and performance are of great concern. In this paper, we introduce a lightweight signal encoding and decomposition method for a low-cost and low-power Visible Light Communication (VLC)-based indoor localization system. Firstly, a Gold-sequence-based tiny-length code selection method is introduced for light encoding. Then a correlation-based asynchronous blind light-signal decomposition method is developed for the decomposition of the lights mixed with modulated light sources. It is able to decompose the mixed light-signal package in real-time. The average decomposition time-cost for each frame is 20 ms. By using the decomposition results, the localization system achieves accuracy at 0.56 m. These features outperform other existing low-cost indoor localization approaches, such as WiFiSLAM.
Visible light communication-based indoor localization using Gaussian process

Kejie Qiu, Fangyi Zhang, and Ming Liu

In IEEE/RSJ International Conference on Intelligent Robots and Systems, Dec 2015

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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.
Visible light communication-based indoor environment modeling and metric-free path planning

Kejie Qiu, Fangyi Zhang, and Ming Liu

In IEEE International Conference on Automation Science and Engineering, Dec 2015

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For mobile robots and position-based services, localization is the most fundamental capability while path-planning is an important application based on that. A novel localization and path-planning solution based on a low-cost 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. Path-planning is hereby feasible by using the GP variance field, rather than using a metric map. Graph-based path-planners are introduced to cope with the practical situations. We demonstrate our path-planning system by real-time experiments performed on a tablet PC in an indoor environment.