用于无人机在动态平台上精确着陆的主动引导:一种视觉惯性方法。
Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-Inertial Approach.
作者信息
Chang Ching-Wei, Lo Li-Yu, Cheung Hiu Ching, Feng Yurong, Yang An-Shik, Wen Chih-Yung, Zhou Weifeng
机构信息
Department of Mechanical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
出版信息
Sensors (Basel). 2022 Jan 5;22(1):404. doi: 10.3390/s22010404.
This work aimed to develop an autonomous system for unmanned aerial vehicles (UAVs) to land on moving platforms such as an automobile or a marine vessel, providing a promising solution for a long-endurance flight operation, a large mission coverage range, and a convenient recharging ground station. Unlike most state-of-the-art UAV landing frameworks that rely on UAV onboard computers and sensors, the proposed system fully depends on the computation unit situated on the ground vehicle/marine vessel to serve as a landing guidance system. Such a novel configuration can therefore lighten the burden of the UAV, and the computation power of the ground vehicle/marine vessel can be enhanced. In particular, we exploit a sensor fusion-based algorithm for the guidance system to perform UAV localization, whilst a control method based upon trajectory optimization is integrated. Indoor and outdoor experiments are conducted, and the results show that precise autonomous landing on a 43 cm × 43 cm platform can be performed.
这项工作旨在开发一种用于无人机(UAV)的自主系统,使其能够降落在移动平台上,如汽车或船舶,为长续航飞行操作、大任务覆盖范围和便捷的充电地面站提供了一个有前景的解决方案。与大多数依赖无人机机载计算机和传感器的先进无人机着陆框架不同,所提出的系统完全依赖于位于地面车辆/船舶上的计算单元作为着陆引导系统。因此,这种新颖的配置可以减轻无人机的负担,并且可以增强地面车辆/船舶的计算能力。特别是,我们为引导系统开发了一种基于传感器融合的算法来进行无人机定位,同时集成了一种基于轨迹优化的控制方法。进行了室内和室外实验,结果表明可以在43厘米×43厘米的平台上实现精确的自主着陆。
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