基于视觉导航的无人机自主精准降落

Autonomous and Precise Landing of UAVs Based on Vision Navigation

针对传统导航方式精度低、误差大等问题,结合视觉导航设计了一种基于ArUco码的着陆标识。对机载相机采集的实时影像进行图像处理,利用世界坐标系与像素坐标系的映射关系建立无人机位姿估计模型,以特征点坐标解算得到当前无人机与着陆标识物之间的相对姿态估计值,设计并融合误差模型进一步提高定位精确性。通过无人机室外实际应用实验证明,设计的降落标志及新型识别算法大大提高了无人机自主降落的精准性,能更好地满足在军事无人机等高精度降落要求场合的应用。

To solve the problems of low precision and large error of traditional navigation modes,a landing sign based on ArUco code is designed in combination with visual navigation.After processing the real-time images collected by the airborne camera,the UAV pose estimation model is established by using the mapping relationship between the world coordinate system and the pixel coordinate system.The estimated value of relative attitude between the UAV and the landing marker is obtained by solving the coordinates of the feature points.The error model is designed and fused to further improve positioning accuracy.Through the outdoor practical application experiment of UAV,it is proved that the designed landing sign and new recognition algorithm greatly improve the accuracy of UAV autonomous landing,which can be better applied to scenarios with high-precision landing requirements such as military UAVs.