The usefulness of sensor fusion for unmanned aerial vehicle indoor positioning

IF 0.8 Q4 ROBOTICS
Hang Guo, Xin Chen, Min Yu, M. Uradziński, Liang Cheng
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引用次数: 0

Abstract

PurposeIn this study, an indoor sensor information fusion positioning system of the quadrotor unmanned aerial vehicle (UAV) was investigated to solve the problem of unstable indoor flight positioning.Design/methodology/approachThe presented system was built on Light Detection and Ranging (LiDAR), Inertial Measurement Unit (IMU) and LiDAR-Lite devices. Based on this, one can obtain the aircraft's current attitude and the position vector relative to the target and control the attitudes and positions of the UAV to reach the specified target positions. While building a UAV positioning model relative to the target for indoor positioning scenarios under limited Global Navigation Satellite Systems (GNSS), the system detects the environment through the NVIDIA Jetson TX2 (Transmit Data) peripheral sensor, obtains the current attitude and the position vector of the UAV, packs the data in the format and delivers it to the flight controller. Then the flight controller controls the UAV by calculating the posture to reach the specified target position.FindingsThe authors used two systems in the experiment. The first is the proposed UAV, and the other is the Vicon system, our reference system for comparison purposes. Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.Originality/valueVicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.
传感器融合在无人机室内定位中的应用
目的针对四旋翼无人机室内飞行定位不稳定的问题,研究了一种室内传感器信息融合定位系统。设计/方法/方法所提出的系统建立在光探测和测距(LiDAR)、惯性测量单元(IMU)和LiDAR-Lite设备上。基于此,可以获得飞机的当前姿态和相对于目标的位置矢量,并控制无人机的姿态和位置以到达指定的目标位置。在有限的全球导航卫星系统(GNSS)下,该系统在建立无人机相对于目标的室内定位模型时,通过NVIDIA Jetson TX2(传输数据)外围传感器检测环境,获得无人机的当前姿态和位置矢量,将数据打包并发送给飞行控制器。然后,飞行控制器通过计算到达指定目标位置的姿态来控制无人机。作者在实验中使用了两个系统。第一个是提出的无人机,另一个是维康系统,这是我们用于比较的参考系统。从低速到高速实验,维康定位误差可以被认为低于2毫米。经过比较,实验结果表明,该系统完全可以满足室内四旋翼无人机飞行实时定位(小于50mm)的要求。与Vicon方法相比,验证了该方法的准确性和鲁棒性,初步达到了室内稳定飞行的目的。从低速到高速实验,原点/值维康定位误差可以被认为低于2毫米。经过比较,实验结果表明,该系统完全可以满足室内四旋翼无人机飞行实时定位(小于50mm)的要求。与Vicon方法相比,验证了该方法的准确性和鲁棒性,初步达到了室内稳定飞行的目的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.50
自引率
0.00%
发文量
21
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