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Optical Flow and Inertial Navigation System Fusion in UAV Navigation

机译:无人机导航中的光流与惯性导航系统融合

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摘要

In recent years navigation on the basis of computation of the camera path and the distance to obstacles with the aid of field of image motion velocities (i.e. optical flow, OF) became highly demanded particularly in the area of relatively small and even micro unmanned aerial vehicles (UAV). Video sequences captured by onboard camera gives the possibility of the OF calculation with the aid of relatively simple algorithms like Lucas-Kanade. The complete OF is the linear function of linear and angular velocities of the UAV which provides an additional means for the navigation parameters estimation. Such UAV navigation approach presumes that on-board camera gives the video sequence of the underlying surface images providing the information about the UAV evolutions. Navigation parameters are extracted on the basis of exact OF formulas which gives the observation process description for estimation based on Kalman filtering. One can expect the high accuracy of the estimated parameters (linear and angular velocities) because their number is substantially less than the number of measurements (practically the number of the camera pixels).
机译:近年来,特别是在相对较小甚至微型的无人飞行器领域,对基于摄像机路径的计算以及借助像运动速度(即光流,OF)到障碍物的距离进行导航的需求越来越高。 (UAV)。车载摄像头捕获的视频序列借助相对简单的算法(如Lucas-Kanade)可以进行OF计算。完整的OF是无人机的线速度和角速度的线性函数,这为导航参数估计提供了额外的手段。这种UAV导航方法假定车载摄像机给出了底层表面图像的视频序列,从而提供有关UAV演变的信息。在精确的OF公式的基础上提取导航参数,该公式为基于卡尔曼滤波的估计提供了观测过程描述。可以预期估计参数(线速度和角速度)的高精度,因为它们的数量大大少于测量的数量(实际上是相机像素的数量)。

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  • 来源
    《Unmanned/unattended sensors and sensor networks XII》|2016年|998606.1-998606.16|共16页
  • 会议地点 Edinburgh(GB)
  • 作者单位

    Institute for Information Transmission Problems RAS, 127051 Bolshoy Karetny per. 19, build. 1, Moscow, Russia;

    Institute for Information Transmission Problems RAS, 127051 Bolshoy Karetny per. 19, build. 1, Moscow, Russia;

    Institute for Information Transmission Problems RAS, 127051 Bolshoy Karetny per. 19, build. 1, Moscow, Russia,Monash University, Wellington Road, Clayton, Victoria, 3800, Australia;

    Institute for Information Transmission Problems RAS, 127051 Bolshoy Karetny per. 19, build. 1, Moscow, Russia;

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