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.

无人机高可靠性着陆系统因其在复杂野外环境中的适用性而受到广泛关注。准确定位、灵活跟踪和可靠回收是无人机着陆的主要挑战。本文提出并实现了一种新型无人机自主着陆系统及其控制框架。它由环境感知系统、无人地面车辆 (UGV) 和用于自主定位、跟踪和回收无人机的 Stewart 平台组成。首先，开发了基于多传感器融合的识别算法，借助一维转台对目标进行实时定位。其次，提出了由UGV和着陆平台组成的双级跟踪策略，用于动态跟踪着陆无人机。从广义上讲，无人车通过人工势场（APF）路径规划和模型预测控制（MPC）跟踪算法负责快速跟踪。而平台控制器采用梯形速度规划来补偿UGV的跟踪误差，实现对无人机小范围内的精确跟踪。此外，Stewart平台还设计了包含姿态补偿控制器和阻抗控制器的恢复算法，保证无人机水平、柔顺着陆。最后，大量的仿真和实验致力于验证所开发的系统和框架的可行性和可靠性，表明它是无人机在草原、坡地、雪地等野外环境自主着陆的优越案例。