Technology Report : Robotic Localization and Navigation System for Visible Light Positioning and SLAM

TL;DR

This paper introduces a multi-sensor fusion approach combining visible light positioning with SLAM techniques, enabling accurate and robust robotic localization and navigation even in LED-scarce environments, verified through extensive real-time experiments.

Contribution

It presents a novel loosely-coupled multi-sensor fusion method integrating VLP, LiDAR, odometry, and camera data for improved indoor robot localization.

Findings

Achieves an average localization accuracy of 2 cm.

Operates with an average computational time of 50 ms on low-cost platforms.

Provides robust localization even with LED shortages or outages.

Abstract

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.