Design of a Mobile Service Robot Mapping System Based on Hector SLAM

Abstract

This research focuses on indoor environment mapping using mobile robots. The unknown environment presents a challenge in robotics. Therefore, the SLAM (Simultaneous Localization and Mapping) method, which has mapping capabilities, is employed to continuously localize the robot's position relative to the map. In this experiment, 2D laser scanning data was obtained using an RPLidar-A1 and processed by the Hector SLAM algorithm, resulting in an occupancy grid map. The experiment involved a mobile robot equipped with a LiDAR sensor, which collected data around the robot as it navigated inside a room, enabling real-time mapping. Upon completion of the experiment, this method successfully mapped the environment around the robot with an average mapping error of 17.67 cm.