Design and Analysis of SLAM-based Autonomous Navigation of Mobile Robot

This work, investigated an autonomous mobile robot simultaneous localization and mapping (SLAM) using the Extended Kalman Filter (EKF) in an indoor environment. All of the experiments were run using the Robot Operating System (ROS). In the actual trials, the 2D laser scan matching data was acquired using the Rplidar A1 single-line lidar, and the indoor map was created using the open-source Gmapping and Hector SLAM algorithms, which may obtain the indoor maps in the ROS graphical tool Rviz. An autonomous mobile robot for simultaneous localization and mapping is possible and high-precision maps may be created, according to the experimental results of the two open-source algorithms with and without sensor fusion analyzed.