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Research on visual navigation technology of unmanned aerial vehicle landing

机译:无人机降落视觉导航技术研究

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Guide the UAV landing by using ground visual navigation system. Firstly, introduce the basic space intersection model: two videos capture sequence images of UAV and two theodolites record the azimuth and elevation of the optical axises of two cameras simultaneously. Then the position of UAV can be obtained by means of intersecting in space. Secondly, propose the adjustment model by introducing adjustment theory to improve the calculation precision. Finally, using kalman filter to improve the position accuracy further. The simulation model of visual navigation system is based on 3ds Max software. The simulation experiments show that, the basic space intersection model has high accuracy; the adjustment model can improve the accuracy in elevation direction; the position accuracy is further improved by introducing of kalman filter. Combining the above models and algorithms, the vision navigation system presented in this article meets the requirements of UAV landing.
机译:使用地面视觉导航系统引导无人机降落。首先介绍基本的空间相交模型:两个视频捕获无人机的序列图像,两个经纬仪同时记录两个摄像机的光轴的方位角和仰角。然后,可以通过在空间上相交来获得无人机的位置。其次,通过引入调整理论提出调整模型,以提高计算精度。最后,使用卡尔曼滤波器进一步提高定位精度。视觉导航系统的仿真模型基于3ds Max软件。仿真实验表明,基本的空间相交模型具有较高的精度。调整模型可以提高仰角方向的精度。通过引入卡尔曼滤波器,可以进一步提高位置精度。结合以上模型和算法,本文提出的视觉导航系统满足了无人机着陆的要求。

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