Image Sensor-Based Three-Dimensional Visible Light Positioning for Various Environments

Area of Science:

• Computer Vision
• Robotics
• Indoor Positioning Systems

Background:

• Visible light positioning (VLP) systems using image sensors (IS) are gaining attention.
• Current IS-based VLP systems struggle with 2D limitations, reliance on inertial measurement units (IMU), and performance degradation under challenging conditions like single LED or decoding failures.

Purpose of the Study:

• To develop a novel three-dimensional (3D) visible light positioning system for enhanced performance across various environments.
• To overcome the limitations of existing 2D positioning systems and improve accuracy when LED signals are weak or absent.

Main Methods:

• Utilized IMU data to determine the receiver's state and 2D position.
• Implemented a height-size curve fitting method to calculate receiver height, avoiding traditional iterative errors.
• Developed a firefly-assisted unscented particle filter (FA-UPF) algorithm for robust positioning during LED signal loss or decoding failures.

Main Results:

• Achieved a positioning error within 10 cm under a single LED condition.
• Demonstrated an average positioning error of 6.45 cm using the FA-UPF algorithm in scenarios with no light source.
• The proposed system offers high-precision dynamic positioning capabilities.

Conclusions:

• The novel IS-based VLP system effectively addresses limitations of existing methods, providing accurate 3D positioning.
• The FA-UPF algorithm significantly enhances positioning reliability and accuracy in challenging, low-light, or signal-absent environments.
• This research contributes to more robust and versatile indoor positioning solutions.