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A Vision-Based Automated Guided Vehicle System with Marker Recognition for Indoor Use

机译:具有视觉识别功能的基于视觉的自动导向车辆系统,用于室内

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We propose an intelligent vision-based Automated Guided Vehicle (AGV) system using fiduciary markers. In this paper, we explore a low-cost, efficient vehicle guiding method using a consumer grade web camera and fiduciary markers. In the proposed method, the system uses fiduciary markers with a capital letter or triangle indicating direction in it. The markers are very easy to produce, manipulate, and maintain. The marker information is used to guide a vehicle. We use hue and saturation values in the image to extract marker candidates. When the known size fiduciary marker is detected by using a bird's eye view and Hough transform, the positional relation between the marker and the vehicle can be calculated. To recognize the character in the marker, a distance transform is used. The probability of feature matching was calculated by using a distance transform, and a feature having high probability is selected as a captured marker. Four directional signals and 10 alphabet features are defined and used as markers. A 98.87% recognition rate was achieved in the testing phase. The experimental results with the fiduciary marker show that the proposed method is a solution for an indoor AGV system.
机译:我们提出了一种使用基准标记的基于视觉的智能自动导引车(AGV)系统。在本文中,我们探索了一种使用消费级网络摄像头和基准标记的低成本,高效的车辆引导方法。在提出的方法中,系统使用带有大写字母或三角形指示其方向的基准标记。标记非常易于生产,操作和维护。标记信息用于引导车辆。我们在图像中使用色相和饱和度值来提取候选标记。当通过使用鸟瞰图和霍夫变换检测到已知尺寸的基准标记时,可以计算标记与车辆之间的位置关系。为了识别标记中的字符,使用了距离变换。通过使用距离变换来计算特征匹配的概率,并且选择具有高概率的特征作为捕获标记。定义了四个方向信号和10个字母特征并将其用作标记。在测试阶段,识别率达到了98.87%。利用基准标记的实验结果表明,该方法是一种室内AGV系统的解决方案。

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