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RFID-based localization system for mobile robot with Markov Chain Monte Carlo

机译:基于马尔可夫链蒙特卡罗的基于RFID的移动机器人定位系统

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This paper proposes a robust and precise localization system for mobile robots with the aid of Radio Frequency Identification (RFID) technology and the Markov Chain Monte Carlo (MCMC) optimization algorithm. By integrating the RFID module, RFID tags, a mobile robot and an off-board computer together, the localization system uses MCMC to analyze RFID signal information and get optimized mobile robot's location information. This paper focuses on explaining the development of RFID sensor model and the processes of building the MCMC algorithm. For sensor model development, the effects of orientation between the RFID reader and RFID tag and the velocity of the mobile robot are investigated. For the MCMC method, a sequential Monte Carlo method is adopted to optimize the result. Finally, the initial experiment results indicate that the proposed localization system has low error and could be used to effectively locate mobile robots.
机译:本文借助射频识别(RFID)技术和马尔可夫链蒙特卡洛(MCMC)优化算法,为移动机器人提出了一种鲁棒且精确的定位系统。通过将RFID模块,RFID标签,移动机器人和车载计算机集成在一起,定位系统使用MCMC来分析RFID信号信息并获得优化的移动机器人的位置信息。本文着重于解释RFID传感器模型的发展以及建立MCMC算法的过程。为了开发传感器模型,研究了RFID阅读器和RFID标签之间的方向以及移动机器人速度的影响。对于MCMC方法,采用顺序蒙特卡罗方法来优化结果。最后,初步的实验结果表明,所提出的定位系统误差低,可有效地定位移​​动机器人。

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