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Accurate Localization of Tagged Objects Using Mobile RFID-Augmented Robots

机译:使用移动RFID增强机器人准确定位标记物体

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This paper studies the problem of tag localization using RFID-augmented robots, which is practically important for promising warehousing applications, e.g., automatic item fetching and misplacement detection. Existing RFID localization systems suffer from one or more of following limitations: requiring specialized devices; only 2D localization is enabled; having blind zone for mobile localization; low scalability. In this paper, we use Commercial Off-The-Shelf (COTS) robot and RFID devices to implement a Mobile RF-robot Localization (MRL) system. Specifically, when the RFID-augmented robot moves along the straight aisle in a warehouse, the reader keeps reading the target tag via two vertically deployed antennas (R-1 and R-2) and returns the tag phase data with timestamps to the server. We take three points in the phase profile of antenna R-1 and leverage the spatial and temporal changes inherent in this phase triad to construct an equation set. By solving it, we achieve the location of target tag relative to the trajectory of antenna R-1. Based on different phase triads, we can have candidate locations of the target tag with different accuracy. Then, we propose theoretical analysis to quantify the deviation of each localization result. A fine-grained localization result can be achieved by assigning larger weights to the localization results with smaller deviations. Similarly, we can also calculate the relative location of target tag with respect to the trajectory of antenna R-2. Leveraging the geometric relationships among target tag and antenna trajectories, we eventually calculate the location of target tag in 3D space. We perform various experiments to evaluate the performance of the MRL system and results show that the proposed MRL system can achieve high accuracy in both 2D and 3D localization.
机译:本文研究了使用RFID增强机器人标签本地化的问题,这对于有前途的仓储应用实际上是重要的,例如,自动项目取样和误操作检测。现有的RFID本地化系统患有以下一个或多个以下限制:需要专用设备;只有2D本地化;盲区用于移动本地化;可扩展性低。在本文中,我们使用商业现成(COTS)机器人和RFID设备来实现移动RF机器人定位(MRL)系统。具体地,当RFID增强的机器人沿着仓库中的直线移动时,读者通过两个垂直部署的天线(R-1和R-2)一直读取目标标签,并将标签相位数据与时间戳返回到服务器。我们在天线R-1的相位轮廓中取三点,并利用该阶段三合会固有的空间和时间变化来构造方程组。通过解决它,我们可以实现相对于天线R-1的轨迹的目标标签的位置。基于不同的相位三合会,我们可以具有不同的准确度的目标标签的候选位置。然后,我们提出了理论分析来量化每个定位结果的偏差。通过将较大的重量分配给定位结果,可以通过较小的偏差来实现细粒度的定位结果。类似地,我们还可以在天线R-2的轨迹方面计算目标标签的相对位置。利用目标标签和天线轨迹之间的几何关系,我们最终计算3D空间中目标标签的位置。我们执行各种实验来评估MRL系统的性能,结果表明,所提出的MRL系统可以在2D和3D本地化中实现高精度。

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