Tightly-Coupled VLP/INS Integrated Navigation by Inclination Estimation and Blockage Handling

TL;DR

This paper presents a tightly coupled VLP/INS navigation system that estimates PD inclination and detects blockages, significantly improving indoor localization accuracy and robustness in real-world scenarios.

Contribution

It introduces a novel graph optimization-based method for joint inclination estimation, blockage detection, and pose estimation in VLP/INS integrated navigation.

Findings

Achieved 10 cm average positioning accuracy in real-world tests.

Estimated inclination within 1 degree despite changes and blockages.

Demonstrated robustness of the system through simulations and experiments.

Abstract

Visible Light Positioning (VLP) has emerged as a promising technology capable of delivering indoor localization with high accuracy. In VLP systems that use Photodiodes (PDs) as light receivers, the Received Signal Strength (RSS) is affected by the incidence angle of light, making the inclination of PDs a critical parameter in the positioning model. Currently, most studies assume the inclination to be constant, limiting the applications and positioning accuracy. Additionally, light blockages may severely interfere with the RSS measurements but the literature has not explored blockage detection in real-world experiments. To address these problems, we propose a tightly coupled VLP/INS (Inertial Navigation System) integrated navigation system that uses graph optimization to account for varying PD inclinations and VLP blockages. We also discussed the possibility of simultaneously estimating the robot's pose and the locations of some unknown LEDs. Simulations and two groups of real-world experiments demonstrate the efficiency of our approach, achieving an average positioning accuracy of 10 cm during movement and inclination accuracy within 1 degree despite inclination changes and blockages.