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A Mobile Robot Localization via Indoor Fixed Remote Surveillance Cameras dagger

机译:通过室内固定遥控监控摄像头匕首的移动机器人定位

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Localization, which is a technique required by service robots to operate indoors, has been studied in various ways. Most localization techniques have the robot measure environmental information to obtain location information; however, this is a high-cost option because it uses extensive equipment and complicates robot development. If an external device is used to determine a robot's location and transmit this information to the robot, the cost of internal equipment required for location recognition can be reduced. This will simplify robot development. Thus, this study presents an effective method to control robots by obtaining their location information using a map constructed by visual information from surveillance cameras installed indoors. With only a single image of an object, it is difficult to gauge its size due to occlusion. Therefore, we propose a localization method using several neighboring surveillance cameras. A two-dimensional map containing robot and object position information is constructed using images of the cameras. The concept of this technique is based on modeling the four edges of the projected image of the field of coverage of the camera and an image processing algorithm of the finding object's center for enhancing the location estimation of objects of interest. We experimentally demonstrate the effectiveness of the proposed method by analyzing the resulting movement of a robot in response to the location information obtained from the two-dimensional map. The accuracy of the multi-camera setup was measured in advance.
机译:本地化是服务机器人在室内运营的技术所需的技术,已经采用各种方式研究。大多数本地化技术都有机器人测量环境信息以获得位置信息;但是,这是一种高成本选项,因为它使用广泛的设备并使机器人开发复杂化。如果使用外部设备来确定机器人的位置并将该信息发送到机器人,则可以减少位置识别所需的内部设备的成本。这将简化机器人开发。因此,本研究提出了一种通过从安装在室内安装的监视摄像机构造的地图来控制机器人来控制机器人的有效方法。只有一个物体的唯一形象,难以遮挡由于遮挡而尺寸。因此,我们提出了一种利用几个相邻监视摄像机的定位方法。使用摄像机的图像构建包含机器人和对象位置信息的二维图。该技术的概念是基于对摄像机覆盖范围的投影图像的四个边缘建模,以及查找对象中心的图像处理算法,用于增强感兴趣对象的位置估计。我们通过分析从二维图获得的位置信息分析机器人的所得到的机器人的所得运动来实验地证明所提出的方法的有效性。预先测量多摄像机设置的精度。

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