Comparison of Two SLAM Algorithms Provided by ROS (Robot Operating System)

Navigation of the mobile Robot is one of the salient aspects of robotics. For a robot to navigate successfully in an environment, a robot needs a map of that environment. Simulation Localization and Mapping (SLAM) is a versatile mapping method that can be used for mapping. This paper investigates two of the SLAM algorithms provided on an open-source framework called the Robotic Operating System (ROS) with other software (RVIZ and Gazebo). This paper aims to compare the result of the two SLAM algorithms (Hector SLAM, GMapping) in terms of map accuracy and the average time taken for the Waffle Pi (robot model) to reach its various destinations in an unknown indoor environment. The distinctiveness of this paper lies in the evaluation of map qualities with respect to the time taken by the Waffle Pi robot to navigate through the Gazebo world environments where dynamic obstacles were introduced.