UAV-Enabled 3D Indoor Positioning and Navigation Based on VLC

The 3D indoor positioning and indoor navigation (IPIN) system is of great significance for promoting and expanding indoor intelligent services and applications. The rapid development of unmanned aerial vehicles (UAVs) has provided new opportunities in this field. However, in contrast to their outdoor applications, IPIN for UAVs is more challenging since the Global Positioning System (GPS) is in general inaccessible in indoor environments. In this work, we propose a UAV-enabled 3D IPIN system based on visible light communication (VLC). Firstly, a novel VLC-based indoor positioning scheme is developed using a fusion algorithm based on the dynamic time warping (DTW) method with visible light intensity sequence (VLIS) and inertial measurement unit (IMU) data. To reduce the workload of fingerprint measurements, we propose to modularize a floor site using a standard symmetric structure for VLC positioning. In this manner, the navigation can be achieved by recognizing the edge of each module. Furthermore, since the sampling frequency of IMU is much higher than that of VLIS, discrete Kalman filter (KF) is introduced to correct the location measured by IMU when VLIS is unavailable. A proof-of-concept IPIN prototype is constructed. Field experiments confirm the effectiveness of our proposed IPIN system.