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A Quantitative Study of Tuning ROS Adaptive Monte Carlo Localization Parameters and their Effect on an AGV Localization

机译:调整ROS自适应蒙特卡洛定位参数及其对AGV定位影响的定量研究。

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One key aspect of the use of Automated Guided Vehicles in an industrial environment is its localization effectiveness. Among the existing techniques, the use of a laser scanner stands out. Besides, the Adaptive Monte Carlo Localization algorithm has become a reference in academic research. Despite many works use the AMCL package, they do not fully discuss the effect of the parameters change on the algorithm response and its tuning. This work aims to examine the distinct influence of each tested parameter in AGV localization. We performed the experiments in the same environment, and the AGV ran the same path to enable comparison against the parameters variation. For the 7 parameters tested, the results show the relationship between the package parameters and the localization response behavior. Although the article does not aim to propose the best parameter tuning, the results show the direction to follow in values adjusting.
机译:在工业环境中使用自动引导车辆的一个关键方面是其本地化有效性。在现有技术中,激光扫描仪的使用非常引人注目。此外,自适应蒙特卡洛定位算法已成为学术研究的参考。尽管有许多工作使用AMCL程序包,但他们没有充分讨论参数更改对算法响应及其调整的影响。这项工作旨在检查AGV本地化中每个测试参数的不同影响。我们在相同的环境中进行了实验,AGV的运行路径相同,可以与参数变化进行比较。对于测试的7个参数,结果显示了封装参数与本地化响应行为之间的关系。尽管本文的目的不是提出最佳参数调整,但结果显示了值调整的方向。

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