融合IMU与单目视觉的无人机自主定位方法

A Method of Autonomous Localization for UAV with Fusion of IMU and Mono SLAM

具备自主定位功能的智能无人机正逐渐成为当前无人机发展的重要趋势。小型与微型无人机的负载、成本与飞行能力有限,无法搭载载重较大的定位系统,而所搭载的低精度IMU无法满足无人机自主定位的需求。利用简便低廉的单目相机构建单目SLAM系统,通过扩展卡尔曼滤波器与低精度IMU信息相融合,可以实时估计单目SLAM系统所生成的稀疏点云地图的真实尺度,并可以较为准确地估计无人机在三维空间中的位姿状态。通过无人机飞行实验,验证了方法的有效性。

It is an important trend in the development of UAV to develop UAVs with the ability of autonomous localization.For small and micro UAVs,due to the limitation of payload,cost,and the ability of flight,it is impossible to fly with the high accuracy but heavy position system and the low accuracy IMU built in small and micro UAVs cannot satisfy the needs of autonomous localization.Mono SLAM system was built with cheap mono camera,fused with the information from IMU of low accuracy based on extended Kaman filter,to estimate the real scale of sparse point cloud map generated by mono slam system and the pose of small and micro UAVs in 3D space.With the experiment of flying,the efficient of the proposed method was approved.