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

Abstract

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.