Active Indoor Localization

GPS does not operate reliably in indoor. Researchers have been working on developing Indoor Positioning System (IPS) for the last two decades. We have been at the forefront of this research by developing novel solutions that can make IPS a reality. Our work on tagged or active localization focuses on using Visible Light Positioning (VLP) techniques. VLP systems can potentially leverage the existing lighting infrastructure of a building and provide localization (e.g., for asset tracking, robotic navigation) as a value-added secondary service. We have developed one of the largest and most advanced VLP system prototypes of the world. The prototype system consists of bespoke VLC luminaires and custom designed tags using single and multiple photodiodes. We have also integrated Virtual Reality (VR) technology, as an automated, accurate ground truth recording system, with our prototype which makes data collection for the training and testing machine learning easy.

Researchers:

  • Tyrel Glass (PhD researcher)
  • Nathaniel Faulkner (PhD researcher)
  • Baden Parr (Student researcher)
  • Adli Hasan (Student researcher)
  • Moi Tin Chew (PhD researcher)
  • Dr Daniel Konings
  • Dr Mathew Legg
  • Prof Serge Demidenko
  • A/P Fakhrul Alam (Research Lead)

Publications in Active Indoor Localisation:

  1. T. Glass, F. Alam, M. Legg, and F. Noble, " Autonomous Fingerprinting and Large Experimental Data Set for Visible Light Positioning," Sensors, May 2021.
  2. M. Chew, F. Alam, M. Legg, and G. S. Gupta, “Accurate Ultrasound Indoor Localization Using Spring-Relaxation Technique”, Electronics, May 2021
  3. A. H. A. Bakar, T. Glass, H. Y. Tee, F. Alam and M. Legg, " Accurate Visible Light Positioning using Multiple Photodiode Receiver and Machine Learning," IEEE Transactions on Instrumentation & Measurement, September 2020.
  4. F. Alam, N. Faulkner, M. Legg and S. Demidenko, " Indoor Visible Light Positioning using Spring-Relaxation Technique in Real-World Setting," IEEE Access, vol. 7, pp. 91347 - 91359, July 2019.
  5. F. Alam, B. Parr, and S. Mander, "Visible Light Positioning Based On Calibrated Propagation Model," IEEE Sensors Letters, vol. 3, no. 2, pp. 1- 4, February 2019.
  6. F. Alam, M.T. Chew, T. Wenge, and G. Sen Gupta, " An Accurate Visible Light Positioning System Using Regenerated Fingerprint Database Based On Calibrated Propagation Model," IEEE Transactions on Instrumentation & Measurement, 2018.
  7. D. Konings, B. Parr, F. Alam, and E. M.-K. Lai, "Falcon: Fused Application of Light based positioning Coupled with Onboard Network localization," IEEE Access, vol. 6, pp. 36155- 36167, 2018.
  8. A. Hasan, T. Glass, F. Alam and M. Legg " Fingerprint-Based Visible Light Positioning using Multiple Photodiode Receiver," Proceedings - 2020 IEEE Sensors Applications Symposium (SAS2020), 2020.
  9. T. Wenge, M. Chew, F. Alam, and G. S. Gupta, "Implementation of a visible light based indoor localization system," in Sensors Applications Symposium (SAS), 2018 IEEE, 2018, pp. 1-6: IEEE.
  10. D. Konings, B. Parr, C. Waddell, F. Alam, K. M. Arif, and E. M.-K. Lai, "HVLP: Hybrid visible light positioning of a mobile robot," in Mechatronics and Machine Vision in Practice (M2VIP), 2017 24th International Conference on, 2017, pp. 1-6: IEEE.
  11. H. Sharifi, A. Kumar, F. Alam and K.M. Arif, “Indoor Localization of Mobile Robot with Visible Light Communication” Proceedings - 12th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, Auckland, 29 Aug 2016 - 31 Aug 2016. 31 Aug 2016.