Calibration of Visible Light Positioning Systems with a Mobile Robot.

Area of Science:

• Robotics and Automation
• Indoor Positioning Systems
• Computer Vision

Background:

• Indoor positioning systems (IPS) often require extensive calibration.
• Visible light positioning (VLP) systems have limited calibration research compared to other IPS like Wi-Fi or UWB.
• Existing VLP calibration methods often rely on known receiver locations or channel models.

Purpose of the Study:

• To develop an automated and accurate calibration procedure for VLP systems.
• To reduce the calibration error in VLP systems.
• To eliminate the need for pre-existing knowledge of light source count or receiver position.

Main Methods:

• Utilized a mobile robot for autonomous data collection in the environment.
• Developed a procedure to map environment including light beacon locations and identities.
• Investigated the impact of robot trajectory, camera resolution, and field of view on calibration accuracy.

Main Results:

• Achieved a significant reduction in positioning error, nearly halving previous results.
• Demonstrated robust performance across various lighting conditions.
• Showcased comparable or superior accuracy to manual calibration methods.

Conclusions:

• The proposed mobile robot-based calibration method enhances VLP system accuracy and efficiency.
• This approach simplifies VLP system deployment by removing the need for manual setup and prior environmental knowledge.
• The findings pave the way for more practical and widespread adoption of VLP technology.