Fixed-Point Landing Method for Unmanned Aerial Vehicles Using Multi-Sensor Pattern Detection

Abstract

Conventional autonomous landing systems for unmanned aerial vehicles (UAVs) mainly rely on global positioning systems (GPS) or a single visual sensor, which identifies specific markers and uses them to guide the UAV landing. However, such methods have low positioning accuracies and weak range recognition abilities, which limit their applicability. This report proposes a fixed-point landing method combining light detection and ranging (LIDAR) technology with a vision camera; the developed approach can be used to locate the landing area and enable a completely autonomous landing, without being affected by distance, weather, or time. First, we establish the mathematical relationship between the color of the mark and the reflection intensity of the laser point cloud. According to this relationship, UAVs can confirm their position relative to the landing point starting from a greater distance without being disturbed by the environmental light intensity. Meanwhile, the method uses the camera to detect the corners of the landing target, even obtaining the relative position at a close distance. Finally, the LIDAR and camera data are combined to detect the corner points of the markers, determine the position of the UAV relative to the center of the landing target in real time, and guide the landing.