Lv Mingming, Fan Bo, Fang Jiwen, Wang Jia
School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China.
Fujian Key Laboratory of Green Intelligent Drive and Transmission for Mobile Machinery, Xiamen 361021, China.
Sensors (Basel). 2024 Mar 2;24(5):1645. doi: 10.3390/s24051645.
Landing on unmanned surface vehicles (USV) autonomously is a critical task for unmanned aerial vehicles (UAV) due to complex environments. To solve this problem, an autonomous landing method is proposed based on a multi-level marker and linear active disturbance rejection control (LADRC) in this study. A specially designed landing board is placed on the USV, and ArUco codes with different scales are employed. Then, the landing marker is captured and processed by a camera mounted below the UAV body. Using the efficient perspective-n-point method, the position and attitude of the UAV are estimated and further fused by the Kalman filter, which improves the estimation accuracy and stability. On this basis, LADRC is used for UAV landing control, in which an extended state observer with adjustable bandwidth is employed to evaluate disturbance and proportional-derivative control is adopted to eliminate control error. The results of simulations and experiments demonstrate the feasibility and effectiveness of the proposed method, which provides an effective solution for the autonomous recovery of unmanned systems.
由于环境复杂，无人机自主降落在无人水面舰艇（USV）上是一项关键任务。为解决这一问题，本研究提出了一种基于多级标记和线性自抗扰控制（LADRC）的自主着陆方法。在无人水面舰艇上放置了一块专门设计的着陆板，并采用了不同尺度的ArUco码。然后，由安装在无人机机身下方的摄像头捕获并处理着陆标记。利用高效的透视n点法估计无人机的位置和姿态，并通过卡尔曼滤波器进一步融合，提高了估计精度和稳定性。在此基础上，采用LADRC进行无人机着陆控制，其中采用带宽可调的扩张状态观测器来评估干扰，并采用比例微分控制来消除控制误差。仿真和实验结果验证了该方法的可行性和有效性，为无人系统的自主回收提供了一种有效的解决方案。
