Technology Report : Robotic Localization and Navigation System for Visible Light Positioning and SLAM
This work addresses the problem of robotic localization and navigation in LED-shortage or outage situations for indoor robotics, representing an incremental improvement over existing VLP methods.
The paper tackled the challenge of robust visible light positioning (VLP) in complex indoor environments by proposing a loosely-coupled multi-sensor fusion method combining VLP, SLAM, LiDAR, odometry, and a rolling shutter camera, achieving an average accuracy of 2 cm and computational time of 50 ms on low-cost embedded platforms.
Visible light positioning (VLP) technology is a promising technique as it can provide high accuracy positioning based on the existing lighting infrastructure. However, existing approaches often require dense lighting distributions. Additionally, due to complicated indoor environments, it is still challenging to develop a robust VLP. In this work, we proposed loosely-coupled multi-sensor fusion method based on VLP and Simultaneous Localization and Mapping (SLAM), with light detection and ranging (LiDAR), odometry, and rolling shutter camera. Our method can provide accurate and robust robotics localization and navigation in LED-shortage or even outage situations. The efficacy of the proposed scheme is verified by extensive real-time experiment. The results show that our proposed scheme can provide an average accuracy of 2 cm and the average computational time in low-cost embedded platforms is around 50 ms.