TY - JOUR
T1 - LedMapper: Toward Efficient and Accurate LED Mapping for Visible Light Positioning at Scale
AU - Liang, Qing
AU - Sun, Yuxiang
AU - Liu, Chengju
AU - Liu, Ming
AU - Wang, Lujia
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant U1713211, in part by the Zhongshan Municipal Science and Technology Bureau Fund under Project ZSST21EG06
Publisher Copyright:
© 1963-2012 IEEE.
PY - 2021/11
Y1 - 2021/11
N2 - Indoor localization of high accuracy has been widely interested. Among competitive solutions, visible light positioning (VLP) is promising due to its ability to deliver high-accuracy 3-D position and orientation with low-cost sensors by sharing the LED lighting infrastructure widespread in buildings. Most VLP systems require a prior LED location map for which manual surveys are costly in practical deployment at scale. In this article, to address this difficulty, we propose a novel system for efficient and accurate offline mapping of LEDs for VLP. With input from visual-inertial sensors and existing or surveyed priors, it builds the map by posing a full simultaneous localization and mapping (SLAM) problem within a factor graph formulation. Compared to manual surveys, it greatly saves human labor and time while yielding an accurate and workspace-aligned LED map. With real-world experiments in a room-scale testbed and a 15times larger lab office, we extensively evaluate the LED mapping system to verify its efficacy and performance gains.
AB - Indoor localization of high accuracy has been widely interested. Among competitive solutions, visible light positioning (VLP) is promising due to its ability to deliver high-accuracy 3-D position and orientation with low-cost sensors by sharing the LED lighting infrastructure widespread in buildings. Most VLP systems require a prior LED location map for which manual surveys are costly in practical deployment at scale. In this article, to address this difficulty, we propose a novel system for efficient and accurate offline mapping of LEDs for VLP. With input from visual-inertial sensors and existing or surveyed priors, it builds the map by posing a full simultaneous localization and mapping (SLAM) problem within a factor graph formulation. Compared to manual surveys, it greatly saves human labor and time while yielding an accurate and workspace-aligned LED map. With real-world experiments in a room-scale testbed and a 15times larger lab office, we extensively evaluate the LED mapping system to verify its efficacy and performance gains.
KW - Factor graph optimization
KW - indoor localization
KW - LED mapping
KW - visible light communication (VLC)
KW - visible light positioning (VLP)
KW - visual-inertial odometry (VIO)
UR - http://www.scopus.com/inward/record.url?scp=85120553948&partnerID=8YFLogxK
U2 - 10.1109/TIM.2021.3123293
DO - 10.1109/TIM.2021.3123293
M3 - Journal article
AN - SCOPUS:85120553948
SN - 0018-9456
VL - 71
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
ER -