Abstract：
The present work proposes a method to characterize, calibrate, and compare, any 2D SLAM algorithm, providing strong statistical evidence, based on descriptive and inferential statistics to bring confidence levels about overall behavior of the algorithms and their comparisons. This work focuses on characterize, calibrate, and compare Cartographer, Gmapping, HECTOR-SLAM, KARTO-SLAM, and RTAB-Map SLAM algorithms. There were four metrics in place: pose error, map accuracy, CPU usage, and memory usage; from these four metrics, to characterize them, Plackett-Burman and factorial experiments were performed, and enhancement after characterization and calibration was granted using hypothesis tests, in addition to the central limit theorem.
摘要：
本工作提出了一种表征方法，校准,比较,任何2DSLAM算法，提供强有力的统计证据，基于描述性和推断性统计，以提供有关算法及其比较的整体行为的置信度。这项工作的重点是表征，校准,比较制图师，Gmapping,Hector-SLAM,KARTO-SLAM,和RTAB-MapSLAM算法。有四个指标：姿势错误，地图精度,CPU使用率,和内存使用；从这四个指标来看，来描述它们的特征，进行了Plackett-Burman和阶乘实验，并在使用假设检验进行表征和校准后进行增强，除了中心极限定理。
