Applicability of visible light communication for positioning and guidance in large indoor spaces

This paper analyses the mobility of Autonomous Guided Vehicles (AGV) in dense industrial environments. VLC technology is exploited to ensure data transmission among the infrastructures and the vehicles, providing X2X links. The VLC technology uses tetrachromatic qhite LEDs for simultaneous lighting and data transmission and dedicated pinpin photodiodes as receivers. Indoors positioning based on VLC methodology provides necessary information to enable guidance services. Coding schemes are designed for each VLC link.
The regulation of the AGVs flow along the lanes inside the warehouse is analyzed as the urban traffic flow using a SUMO urban mobility simulator. This tool is used to generate data related to the AGV movement, and a reinforcement learning scheme, combining agent-based modeling and VLC queuing/request/response behaviors, effectively schedules routes. This provides efficient travel and avoids crowded regions. The demonstration of this proof-of-concept is supported on the evaluation of travel time and traffic flows.