Indoor Positioning Systems (IPSs) have multiple applications. For example, they can be used to guide people, to locate items in a warehouse and to support the navigation of Automated Guided Vehicles (AGV). Currently most AGVs use local pre-defined navigation systems, but they lack a global localisation system. Integrating both systems is uncommon due to the inherent challenge in balancing accuracy with coverage. Visible Light Position (VLP) offers accurate and fast localisation, but it encounters scalability limitations. To overcome this, this paper presents a novel Image Sensor-based VLP (IS-VLP) identification method that harnesses existing Light Emitting Diode (LED) lighting infrastructure to substitute both navigation and localisation systems effectively in the whole area. We developed an IPS that achieves six-axis positioning at 90 Hz refresh rate using OpenCV’s solvePnP algorithm and embedded computing. This IPS has been validated in a laboratory environment and successfully deployed in a real factory to position an operative AGV. The system has resulted in accuracies better than 12 cm for 95% of the measurements. This work advances towards positioning VLP as an appealing choice for IPS in industrial environments, offering an inexpensive, scalable, accurate and robust solution.This research received funding from the Departament de Recerca de Universitats de la
Generalitat de Catalunya under grant 2021 SGR 01524, from the European Union’s Horizon 2020
research and innovation programme under Grant Agreement No. 957246 (project IoT-NGIN) and
from the Spanish MCIN/AEI/10.13039/501100011033 through project PID2019-106808RAI00.Peer ReviewedPostprint (published version
