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通过图像进行无人机的3D定位

Jianxing Yang¹, Enhui Zheng¹, Jiqi Fan¹

¹School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.

Sensors (Basel, Switzerland)

|September 14, 2024

概括

这项研究解决了无人机在无GPS环境中的导航挑战. 它引入了一种新的方法,使用单个图像来准确地确定无人机的高度和定位,而无需卫星支持.

科学领域:

计算机视觉计算机视觉
机器人技术机器人技术机器人技术
地理空间分析是什么

背景情况:

无人机传统上依靠卫星导航 (GPS) 进行定位和高度.
拒绝GPS的环境会破坏卫星通信,挑战传统的无人机导航方法.
准确的无人机定位和高度估计对于安全有效的操作至关重要.

研究的目的:

开发一种无人机定位和高度确定方法,独立于卫星信号.
评估拟议的多尺度输入网络的性能,用于无人机导航在GPS被拒绝的场景.
为了使无人驾驶飞行器 (UAV) 能够基于单一图像的高度判断.

主要方法:

创建了一个无人机数据集,在80-200米之间的高度捕获.
开发和应用一个用于定位的多尺度输入网络.
实现无人机图像与卫星图像对应用于定位.
使用图像衍生的真实空间面积和光学相机参数计算无人机飞行高度.

主要成果:

拟议的定位指数 (RDS) 获得了76.3分.
在20米以内的定位精度达到81.7%的速度.
该方法计算的无人机飞行高度在80-200米范围内,相对错误率为18.1%.
使用单个无人机图像成功进行了高度判断.

结论:

拟议的方法为无人机导航在没有GPS的环境中提供了可行的解决方案.
基于图像的高度确定和定位在没有外部传感器数据的情况下是可行的.
这种方法增强了无人机在具有挑战性的条件下的自主性和操作能力.

关键词:

深度学习是一种深度学习.无人机高度计算方法定位定位定位定位无人驾驶飞行器 (UAV) 是一种无人驾驶飞行器.

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