基于ID标签和WEB摄像头的移动机器人定位

Weiguo Lin, S. Jia, T. Abe, K. Takase
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引用次数: 25

摘要

定位是移动机器人最重要的基础之一。一个成本低、易于实现、简单、有效和鲁棒性强的定位系统一直是研究人员追求的目标。本文提出了一种基于身份标签和网络摄像头的移动机器人定位方法。在我们的方法中,室内环境中的路径映射用节点树表示,每个节点用两个地标表示:ID标签和相同颜色的卡片。在不同位置的天花板上粘贴成对的两个地标,每个节点中每对地标的中点表示该节点的绝对位置,或者由于标签的ID唯一,因此该节点的绝对位置可以用节点的绝对位置和相对于该节点的位置和方向来表示。定位分为两个步骤:通过射频通信检测节点上的ID标签,通过摄像头测量移动机器人相对于该节点的位置和方向。本文总结了相关工作,介绍了该方法的优点,详细描述了系统的方案,讨论了一种从背景中提取地标的快速图像处理算法和系统鲁棒性策略。定位实验表明,该方法的相对位置和方位误差分别小于2.5 cm和2.5度。导航向我们展示了使用ID标签和网络摄像头进行定位在室内环境下导航是可行的。最后,对系统的改进策略进行了探讨。
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Localization of mobile robot based on ID tag and WEB camera
Localization is one of the most important fundament for mobile robot. A localization system with low cost, easy accomplishment, simplicity, effectiveness and robustness is the aim of researchers all the time. Here, we proposed a novel method for localization of mobile robot using ID tag and Web camera. In our method, the path map in an indoor environment is expressed with node tree, every node is represented with two landmarks: ID tag and card with the same colour. Pairs of two landmarks are affixed to ceiling of distinct locations, and the middle point of every pair of landmarks in a node indicates the absolute position or the node because of the unique ID of tag, the absolute position of mobile robot can be expressed with the absolute position of node and, position and orientation relative to this node. Localization is implemented with two steps: detecting ID tag in one node with RF communication and measuring position and orientation of mobile robot relative to this node with camera. In this paper, related works are summarized and the advantages of our method are introduced, the scheme of system is described in detail, a fast image processing algorithm for extracting landmarks from background and strategies for system robustness are discussed. Localization experiments show that with this method the errors or relative position and orientation are less than 2.5 cm and 2.5 degree. Navigation showed us that localization with ID tag and Web camera is feasible for navigation in indoor environment. At last, strategies for improving system are discussed.
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