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基于湖面移动着的着陆平台的系留多旋翼和垂直起降无人机的精确定位着陆测试

Precision Landing Tests of Tethered Multicopter and VTOL UAV on Moving Landing Pad on a Lake.

机构信息

Robotics and Mechatronics Department, Faculty of Mechanical Engineering, Bialystok University of Technology, Wiejska St. 45C, 15-351 Bialystok, Poland.

Automatic Control and Robotics Department, Faculty of Electrical Engineering, Bialystok University of Technology, Wiejska St. 45C, 15-351 Bialystok, Poland.

出版信息

Sensors (Basel). 2023 Feb 10;23(4):2016. doi: 10.3390/s23042016.

Abstract

Autonomous take-off and landing on a moving landing pad are extraordinarily complex and challenging functionalities of modern UAVs, especially if they must be performed in windy environments. The article presents research focused on achieving such functionalities for two kinds of UAVs, i.e., a tethered multicopter and VTOL. Both vehicles are supported by a landing pad navigation station, which communicates with their ROS-based onboard computer. The computer integrates navigational data from the UAV and the landing pad navigational station through the utilization of an extended Kalman filter, which is a typical approach in such applications. The novelty of the presented system is extending navigational data with data from the ultra wide band (UWB) system, and this makes it possible to achieve a landing accuracy of about 1 m. In the research, landing tests were carried out in real conditions on a lake for both UAVs. In the tests, a special mobile landing pad was built and based on a barge. The results show that the expected accuracy of 1 m is indeed achieved, and both UAVs are ready to be tested in real conditions on a ferry.

摘要

自主起飞和在移动着陆垫上降落是现代无人机的非常复杂和具有挑战性的功能,特别是如果它们必须在有风的环境中执行。本文介绍了专注于实现两种无人机(即系绳多旋翼机和 VTOL)的此类功能的研究。这两种车辆都由一个着陆垫导航站支持,该导航站通过使用扩展卡尔曼滤波器与基于 ROS 的机载计算机进行通信。计算机通过使用扩展卡尔曼滤波器将来自无人机和着陆垫导航站的导航数据集成在一起,这是此类应用中的典型方法。所提出系统的新颖之处在于通过超宽带 (UWB) 系统的数据扩展导航数据,这使得实现约 1 米的着陆精度成为可能。在研究中,针对两种无人机在湖上的真实条件进行了着陆测试。在测试中,建造了一个特殊的移动着陆垫,其基于驳船。结果表明,确实达到了预期的 1 米精度,并且两种无人机都已准备好在渡轮上的真实条件下进行测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e54/9964198/813c4201c2f3/sensors-23-02016-g001.jpg

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