Intelligent Visible Light Positioning and Navigation for Indoor and Underground Scenarios
ID:500 View Protection:ATTENDEE Updated Time:2022-05-23 14:31:05 Hits:1676 Oral Presentation

Start Time:2022-05-27 10:10(Asia/Shanghai)

Duration:20min

Session:S5 Intelligent Equipment and Technology » S5-2Intelligent Equipment and Technology-2

No files

Abstract
In the past decade, positioning and navigation for indoor and underground scenarios have been a hot research topic. The Global Navigation Satellite System (GNSS) is the primary system for outdoor scenarios. However, there is no dominant technology for indoor and underground scenarios. Visible light positioning shows its potential for indoor and underground positioning due to its important features, such as high bandwidth for high-speed transmission, energy-efficient, long lifetime, and cost-efficiency. This presentation covers our works to improve the accuracy and robustness of the visible light positioning. The first effort is to reduce the effects of the environment light and noise on the visible light positioning system, which has been hardly focused on before. Then, we try different data fusion methods, including non-linear smoother, non-linear optimization, and machine learning algorithms, to improve the performance of the visible light positioning system. The preliminary results show the proposed visible light positioning system can achieve centimeter-level accuracy for indoor and underground scenarios. In the future, we will further evaluate this technology for large indoor and underground experimental areas. Furthermore, We will integrate the visible light positioning with other techonogies, such as inertial navigation and SLAM for higher performance.
Keywords
visible light positioning;navigation;indoor navigation;intelligent positioning
Speaker
Yuan ZHUANG
Professor Wuhan University

Yuan Zhuang is a professor and the founder of the Sensing, Navigation & Artificial Intelligence Lab (SNAIL) at the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, China. He received the Ph.D. degree in geomatics engineering from the University of Calgary, Canada in 2015. His current research interests include multi-sensors integration, SLAM, wireless localization, Internet of Things (IoT), and machine learning for navigation applications. To date, he has co-authored over 100 academic papers and over 20 patents and has received over 10 academic awards. He is on the editorial board of Satellite Navigation and IEEE Access, the guest editor of the IEEE Internet of Things Journal, and a reviewer of over 20 IEEE journals.

Submit Comment
Verify Code Change Another
All Comments
Important Date
  • Conference Date

    May 26

    2022

    to

    May 27

    2022

  • May 03 2022

    Draft paper submission deadline

  • May 26 2022

    Contribution Submission Deadline

  • May 28 2022

    Registration deadline

Sponsored By
China University of Mining and Technology
Contact Information