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Using RFID Snapshots for Mobile RobotSelf-Localization

机译:使用RFID快照进行移动机器人自我定位

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In recent years, radio frequency identification (RFID) has found its way into the field of mobile robot navigation. On the one hand, the technology promises to contribute solutions to common problems in self-localization and mapping such as the data association problem. On the other hand, questions like how to cope with poor or even missing range and bearing information remain open. In this paper, we present a novel method which tackles these challenges: Inspired by vision-based self-localization approaches, it utilizes RFID snapshots for the estimation of the robot pose. Our experiments show that the new technique enables a robot to successfully localize itself in an indoor environment. The accuracy is comparable to the one of a previous approach using an explicit model of detection probabilities. Our method, however, requires fewer iterations of the underlying particle filter in order to converge to the approximate robot pose.
机译:近年来,射频识别(RFID)已进入移动机器人导航领域。一方面,该技术有望为自定位和映射中的常见问题(例如数据关联问题)提供解决方案。另一方面,诸如如何应对不良甚至不足的射程和方位信息之类的问题仍然悬而未决。在本文中,我们提出了一种解决这些挑战的新颖方法:受基于视觉的自定位方法的启发,它利用RFID快照来估算机器人姿态。我们的实验表明,这项新技术使机器人能够在室内环境中成功定位自己。准确性与使用显式检测概率模型的先前方法相当。但是,我们的方法需要较少的底层粒子滤波器迭代,才能收敛到近似的机器人姿态。

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