A Low-Altitude UAV Dataset Based on Visual–Inertial Navigation

IF 4.3 2区综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Sensors Journal Pub Date : 2024-11-05 DOI:10.1109/JSEN.2024.3488289

Pin Lyu;Chengyou Yong;Jizhou Lai;Cheng Yuan;Qianqian Zhu;Adong Han

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引用次数: 0

Abstract

As unmanned aerial vehicles (UAVs) are increasingly utilized in operational domains ranging from 50 to 500 m, there is a growing need for robust and reliable autonomous positioning, particularly in scenarios where satellite signals are unavailable. To address this challenge, we present a set of visual–inertial datasets collected by low-altitude UAVs. The dataset includes stereo cameras, an inertial measurement unit (IMU), a laser ranging sensor, and RTK-based ground truth. All these sensors have been calibrated and synchronized. The dataset consists of 28 sequences captured across diverse scenarios. To the best of our knowledge, this is the first UAV visual navigation dataset to encompass such a wide range of flight altitudes. Furthermore, we have evaluated the dataset using state-of-the-art visual–inertial simultaneous localization and mapping (SLAM) algorithms. The results demonstrate that existing solutions perform inadequately in certain situations. For the benefit of the research community, we make this dataset publicly accessible. The webpage of our dataset is https://github.com/boomzoeycy/A-Low-Altitude-UAV-Dataset-based-on-Visual-Inertial-Navigation .

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基于视觉惯性导航的低空无人机数据集

随着无人驾驶飞行器（uav）越来越多地应用于50至500米的作战领域，对强大可靠的自主定位的需求日益增长，特别是在卫星信号不可用的情况下。为了解决这一挑战，我们提出了一组由低空无人机收集的视觉惯性数据集。该数据集包括立体摄像机、惯性测量单元（IMU）、激光测距传感器和基于rtk的地面真相。所有这些传感器都经过校准和同步。该数据集由28个序列组成，这些序列来自不同的场景。据我们所知，这是第一个涵盖如此广泛飞行高度的无人机视觉导航数据集。此外，我们使用最先进的视觉惯性同步定位和映射（SLAM）算法对数据集进行了评估。结果表明，现有的解决方案在某些情况下表现不佳。为了研究界的利益，我们公开了这个数据集。我们数据集的网页是https://github.com/boomzoeycy/A-Low-Altitude-UAV-Dataset-based-on-Visual-Inertial-Navigation。

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

IEEE Sensors Journal 工程技术-工程：电子与电气

CiteScore

7.70

自引率

14.00%

发文量

2058

审稿时长

5.2 months

期刊介绍： The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice