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Correction of Inertial Navigation System’s Errors by the Help of Video-Based Navigator Based on Digital Terrarium Map

机译:基于数字玻璃容器地图的基于视频的导航仪对惯性导航系统误差的校正

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This paper deals with the error analysis of a novel navigation algorithm that uses as input the sequence of images acquired from a moving camera and a Digital Terrain (or Elevation) Map (DTM/DEM). More specifically, it has been shown that the optical flow derived from two consecutive camera frames can be used in combination with a DTM to estimate the position, orientation and ego-motion parameters of the moving camera. As opposed to previous works, the proposed approach does not require an intermediate explicit reconstruction of the 3D world. In the present work the sensitivity of the algorithm outlined above is studied. The main sources for errors are identified to be the optical-flow evaluation and computation, the quality of the information about the terrain, the structure of the observed terrain and the trajectory of the camera. By assuming appropriate characterization of these error sources, a closed form expression for the uncertainty of the pose and motion of the camera is first developed and then the influence of these factors is confirmed using extensive numerical simulations. The main conclusion of this paper is to establish that the proposed navigation algorithm generates accurate estimates for reasonable scenarios and error sources, and thus can be effectively used as part of a navigation system of autonomous vehicles.
机译:本文处理了一种新颖的导航算法的误差分析,该算法使用从移动摄像机和数字地形(或高程)地图(DTM / DEM)获取的图像序列作为输入。更具体地说,已经表明,可以将源自两个连续摄像机帧的光流与DTM结合使用,以估计移动摄像机的位置,方向和自我运动参数。与以前的工作相反,提出的方法不需要对3D世界进行中间的显式重建。在本工作中,研究了上述算法的敏感性。识别错误的主要来源是光流评估和计算,有关地形的信息的质量,观察到的地形的结构以及照相机的轨迹。通过假设这些误差源的适当特征,首先针对相机的姿势和运动的不确定性开发出一种闭式表达式,然后使用大量的数值模拟来确认这些因素的影响。本文的主要结论是要确定所提出的导航算法能够为合理的情景和误差源生成准确的估计,从而可以有效地用作自动驾驶汽车导航系统的一部分。

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