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基于超宽带和惯性测量单元的无人机平台自主着陆辅助系统

UWB and IMU-Based UAV's Assistance System for Autonomous Landing on a Platform.

作者信息

Ochoa-de-Eribe-Landaberea Aitor, Zamora-Cadenas Leticia, Peñagaricano-Muñoa Oier, Velez Igone

机构信息

CEIT-Basque Research and Technology Alliance (BRTA), Manuel Lardizabal 15, 20018 San Sebastián, Spain.

Tecnun School of Engineering, Universidad de Navarra, Manuel Lardizabal 13, 20018 San Sebastián, Spain.

出版信息

Sensors (Basel). 2022 Mar 18;22(6):2347. doi: 10.3390/s22062347.

DOI:10.3390/s22062347
PMID:35336532
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8948988/
Abstract

This work presents a novel landing assistance system (LAS) capable of locating a drone for a safe landing after its inspection mission. The location of the drone is achieved by a fusion of ultra-wideband (UWB), inertial measurement unit (IMU) and magnetometer data. Unlike other typical landing assistance systems, the UWB fixed sensors are placed around a 2 × 2 m landing platform and two tags are attached to the drone. Since this type of set-up is suboptimal for UWB location systems, a new positioning algorithm is proposed for a correct performance. First, an extended Kalman filter (EKF) algorithm is used to calculate the position of each tag, and then both positions are combined for a more accurate and robust localisation. As a result, the obtained positioning errors can be reduced by 50% compared to a typical UWB-based landing assistance system. Moreover, due to the small demand of space, the proposed landing assistance system can be used almost anywhere and is deployed easily.

摘要

这项工作提出了一种新型着陆辅助系统（LAS），该系统能够在无人机完成检查任务后为其定位以实现安全着陆。无人机的定位是通过融合超宽带（UWB）、惯性测量单元（IMU）和磁力计数据来实现的。与其他典型的着陆辅助系统不同，UWB固定传感器放置在一个2×2米的着陆平台周围，并且在无人机上附着了两个标签。由于这种设置对于UWB定位系统而言并非最优，因此提出了一种新的定位算法以实现正确的性能。首先，使用扩展卡尔曼滤波器（EKF）算法计算每个标签的位置，然后将两个位置结合起来以实现更准确、更稳健的定位。结果，与典型的基于UWB的着陆辅助系统相比，所获得的定位误差可降低50%。此外，由于对空间的需求较小，所提出的着陆辅助系统几乎可以在任何地方使用，并且易于部署。

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