基于视觉导引的固定翼无人机自主着陆算法研究

Autonomous Landing Algorithm of Fixed-Wing Unmanned Aerial Vehicle Based on Visual Guidance

研究了使用视觉导引系统进行固定翼无人机自主着陆时的相关问题,主要针对提高视觉导航系统获取导航参数的速度及精度展开研究。视觉导航系统获取参数分为两步:跑道检测识别、固定翼无人机相对位姿估计。提高导航系统参数获取速度,主要通过提高耗时较高的跑道检测识别算法的检测识别效率来完成。利用跑道在序列图像中的时空一致性进行候选区域提取,在不影响召回率的情形下减少无效候选区域,从而提高跑道检测效率,最终提高视觉导引系统获取导引参数的速度。为提高估计的导引参数精度,结合跑道上的点线特征进行位姿估计,通过增加可利用的特征数量来提高位姿估计精度。实验仿真结果表明,所提方法有效提高了视觉导航系统获取导航参数的速度及精度。

This paper studies the use of visual guidance system for autonomous landing of fixed-wing unmanned aerial vehicles(UAVs).The research is mainly aimed at improving the speed and accuracy of the visual navigation system to obtain the navigation parameters.The acquisition of parameters by the visual navigation system can be divided into two steps:runway detection and recognition,and relative pose estimation of fixed-wing UAVs.To improve the acquisition speed of navigation system parameters,we mainly improve the detection and recognition efficiency of the time-consuming runway detection and recognition algorithm.In this paper,the spatiotemporal consistency of the runway in the sequence image is used to extract candidate regions,and the invalid candidate regions are reduced without affecting the recall rate.Then the efficiency of runway detection is improved and ultimately the speed of the visual guidance system to obtain guidance parameters is improved.In order to improve the accuracy of the estimated guidance parameters,this paper combines the point and line features on the runway for pose estimation.That improves the pose estimation accuracy by increasing the number of available features.The experimental results show that the proposed method can effectively improve the speed and accuracy of the visual navigation system to obtain the navigation parameters.