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An improved graph-based visual localization system for indoor mobile robot using newly designed markers

机译:一种改进的基于图形的视觉定位系统,用于室内移动机器人,使用新设计的标记

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To address the localization problem for a mobile robot in an indoor environment, an improved visual localization system based on artificial markers is proposed in this article. First, we will present a novel artificial marker which can be detected and identified easily and correctly. We will then introduce how it is designed, recognized, and verified. The markers are arranged on the ceiling and the mobile robot moves around on the ground to capture images with an up-facing monocular camera. The markersa?? information, including the position and direction, will be obtained by processing the images. The cameraa??s uncertainty model is then put forward based on the distortion of the camera. The uncertainty of the obtained markersa?? information is analyzed through the uncertainty model. Finally, with the obtained information, the marker map in global image coordinate system is established and optimized through a graph-based algorithm in which the edges can be updated to reduce the uncertainty using Bayes Estimation method. To verify the effectiveness of the localization system, numerous experiments have been conducted. Additionally, the proposed method has also been applied to industrial forklift to test its robustness in a factory environment.
机译:为了解决室内环境下移动机器人的定位问题,本文提出了一种基于人工标记的改进视觉定位系统。首先,我们将介绍一种新型的人工标记,可以轻松,正确地对其进行检测和识别。然后,我们将介绍如何设计,识别和验证它。这些标记被布置在天花板上,移动机器人在地面上四处移动以使用面向上的单眼相机捕获图像。标记物?通过处理图像将获得包括位置和方向在内的信息。然后根据摄像机的畸变提出摄像机的不确定性模型。获得的标志物的不确定性通过不确定性模型分析信息。最后,利用获得的信息,通过基于图的算法建立并优化全局图像坐标系中的标记图,其中可以使用贝叶斯估计方法更新边缘以减少不确定性。为了验证定位系统的有效性,已经进行了许多实验。另外,所提出的方法也已经应用于工业叉车,以在工厂环境中测试其坚固性。

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