Visible Light Communication-based indoor localization using Gaussian Process

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.

[1]  Ming Liu,et al.  Asynchronous blind signal decomposition using tiny-length code for Visible Light Communication-based indoor localization , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[2]  Qiang Xu,et al.  AccuLoc: practical localization of performance measurements in 3G networks , 2011, MobiSys '11.

[3]  Toshiya Tanaka,et al.  New Position Detection Method Using Image Sensor and Visible Light LEDs , 2009, 2009 Second International Conference on Machine Vision.

[4]  Wan-Young Chung,et al.  VLC-BASED MEDICAL HEALTHCARE INFORMATION SYSTEM , 2012 .

[5]  Roland Siegwart,et al.  Visual Homing From Scale With an Uncalibrated Omnidirectional Camera , 2013, IEEE Transactions on Robotics.

[6]  C. Patrick Yue,et al.  Towards indoor localization using Visible Light Communication for consumer electronic devices , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Guillermo del Campo,et al.  A VLC-based beacon location system for mobile applications , 2013, 2013 International Conference on Localization and GNSS (ICL-GNSS).

[8]  Ming Liu,et al.  Visible light communication-based indoor environment modeling and metric-free path planning , 2015, 2015 IEEE International Conference on Automation Science and Engineering (CASE).

[9]  Carl E. Rasmussen,et al.  Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.

[10]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[11]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[12]  G.B. Giannakis,et al.  Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks , 2005, IEEE Signal Processing Magazine.

[13]  Mohsen Kavehrad,et al.  Indoor positioning algorithm using light-emitting diode visible light communications , 2012 .

[14]  Sang-Kook Han,et al.  An Indoor Visible Light Communication Positioning System Using a RF Carrier Allocation Technique , 2013, Journal of Lightwave Technology.

[15]  Yuxiang Sun,et al.  WiFi signal strength-based robot indoor localization , 2014, 2014 IEEE International Conference on Information and Automation (ICIA).

[16]  Neil D. Lawrence,et al.  WiFi-SLAM Using Gaussian Process Latent Variable Models , 2007, IJCAI.

[17]  S. Haruyama,et al.  High-accuracy positioning system using visible LED lights and image sensor , 2008, 2008 IEEE Radio and Wireless Symposium.

[18]  Anthony Stentz,et al.  Optimal and efficient path planning for partially-known environments , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[19]  Ming Liu,et al.  Environment Modeling-based Indoor Localization using Visible Light Communication , 2015 .

[20]  Max Q.-H. Meng,et al.  Real-Time Multisensor Data Retrieval for Cloud Robotic Systems , 2015, IEEE Transactions on Automation Science and Engineering.

[21]  Roland Siegwart,et al.  DP-FACT: Towards topological mapping and scene recognition with color for omnidirectional camera , 2012, 2012 IEEE International Conference on Robotics and Automation.

[22]  Roland Siegwart,et al.  Scene recognition with omnidirectional vision for topological map using lightweight adaptive descriptors , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Fawzi Nashashibi,et al.  Platoon Control Using VLC: A Feasibility Study. , 2013 .

[24]  Guillermo del Campo,et al.  VLC-based light-weight portable user interface for in-house applications , 2011, 2011 IEEE Consumer Communications and Networking Conference (CCNC).

[25]  Roland Siegwart,et al.  Scale-only visual homing from an omnidirectional camera , 2012, 2012 IEEE International Conference on Robotics and Automation.