Abstract

Visible light positioning (VLP) is a promising technology since it can provide high accuracy indoor localization based on the existing lighting infrastructure. However, existing approaches often require dense LED distributions and persistent line-of-sight (LOS) between transmitter and receiver. What's more, sensors are imperfect, and their measurements are prone to errors. Through multi sensors fusion, we can compensate the deficiencies of stand-alone sensors and provide more reliable pose estimations. In this work, we propose a loosely-coupled multi-sensor fusion method based on VLP and Simultaneous Localization and Mapping (SLAM), using light detection and ranging (LiDAR), odometry, and rolling shutter camera. Our multi-sensor localizer can provide accurate and robust robot localization and navigation in LED shortage/outage situations. The experimental results show that our proposed scheme can provide an average accuracy of 2.5 cm with around 42 ms average positioning latency.

Single LED positioning scheme based on angle sensors in robotics

Linyi Huang, Shangsheng Wen, Zihong Yan, Hongzhan Song, Shuomiao Su, and Weipeng Guan
Appl. Opt. 60(21) 6275-6287 (2021)

Tightly-coupled fusion of iGPS measurements in optimization-based visual SLAM

Ze Yang, Yanyan Li, Jiarui Lin, Yanbiao Sun, and Jigui Zhu
Opt. Express 31(4) 5910-5926 (2023)

Biomimetic navigation system using a polarization sensor and a binocular camera

Jinshan Li, Jinkui Chu, Ran Zhang, Hanpei Hu, Kun Tong, and Jin Li
J. Opt. Soc. Am. A 39(5) 847-854 (2022)

Vehicle positioning scheme based on particle filter assisted single LED visible light positioning and inertial fusion

Jing He and Yang Liu
Opt. Express 31(5) 7742-7752 (2023)

FPP-SLAM: indoor simultaneous localization and mapping based on fringe projection profilometry

Yang Zhao, Haotian Yu, Kai Zhang, Yucheng Zheng, Yi Zhang, Dongliang Zheng, and Jing Han
Opt. Express 31(4) 5853-5871 (2023)