Simultaneous Localization and Mapping for Mobile Robot Using a Single 2D LiDAR Sensor

Abstract

This paper presents the development and validation of a cost-effective mobile robotic platform that performs Simultaneous Localization and Mapping (SLAM) using a single 2D Light Detection and Ranging (LiDAR) sensor. While traditional SLAM systems often rely on expensive 3D LiDAR or computationally intensive visual sensors, this study proposes a novel approach combining a 2D LiDAR mounted on a servo-controlled gimbal to emulate 3D scanning capabilities. The Robot Operating System (ROS) is employed for modular development, integrating packages such as Gmapping for mapping and the Navigation Stack for autonomous movement. The platform features an omnidirectional base to enhance maneuverability. All experiments are conducted in the STDR simulator, providing a realistic environment to assess SLAM and navigation capabilities. Results demonstrate accurate map generation, reliable path planning via the Time Elastic Band (TEB) planner, and consistent obstacle avoidance. The findings validate the feasibility of using cost-effective hardware for advanced robotic functions, promoting broader adoption in industrial and research domains.