A UAV Autonomous Landing System Integrating Locating, Tracking, and Landing in the Wild Environment

Abstract

High-reliability landing systems for unmanned aerial vehicles (UAVs) have gained extensive attention for their applicability in complex wild environments. Accurate locating, flexible tracking, and reliable recovery are the main challenges in drone landing. In this paper, a novel UAV autonomous landing system and its control framework are proposed and implemented. It's comprised of an environmental perception system, an unmanned ground vehicle (UGV), and a Stewart platform to locate, track, and recover the drone autonomously. Firstly, a recognition algorithm based on multi-sensor fusion is developed to locate the target in real time with the help of a one-dimensional turntable. Secondly, a dual-stage tracking strategy composed of a UGV and a landing platform is proposed for dynamically tracking the landing drone. In a wide range, the UGV is in charge of fast-tracking through the artificial potential field (APF) path planning and the model predictive control (MPC) tracking algorithms. While the trapezoidal speed planning is employed in platform controller to compensate for the tracking error of the UGV, realizing the precise tracking to the drone in a small range. Furthermore, a recovery algorithm including an attitude compensation controller and an impedance controller is designed for the Stewart platform, ensuring horizontal and compliant landing of the drone. Finally, extensive simulations and experiments are dedicated to verifying the feasibility and reliability of the developed system and framework, indicating that it is a superior case of UAV autonomous landing in wild environments such as grasslands, slopes, and snow.