Optimization of SLAM Gmapping based on Simulation

Abstract

This paper presents the Optimization of Simultaneous Localization and Mapping (SLAM) Gmapping algorithm, and compare the results of experiments based on the optimized parameters. From the known types of SLAM, we analyze Gmapping, and used the dataset and the ground truth standard map to carry out the experimental results in the simulation. Using the dataset result as a reference, and optimizing the parameters, we have different simulation results. We conducted The optimization and testing experiments in two ways, at first optimizing parameters separately, and second optimizing more than one at a time. This enables us to conclude the preferable way of optimizing parameters which led the close map result to dataset map or ground truth.