(Mapping of a specific area with an autonomous vehicle)

The subject of this study is the SLAM (Simultaneous Localization And Mapping) robot, which can move autonomously and reach determined targets by avoiding obstacles. Ubuntu 24.04.6 operating system and ROS (Robot Operating System) Noetic distribution were used on Raspberry Pi. The software required for the robot to perform its basic functions has been developed on the ROS framework. ROS enables the robot to collect sensor data, process this data, and send commands to the motors. SLAM algorithms were used for mapping and positioning. A 2D map of the environment was generated using lidar data with the Gmapping algorithm, and the location of the robot was visualized precisely with AMCL (Adaptive Monte Carlo Localization). In order for the robot to avoid obstacles, obstacles were detected using lidar data and appropriate commands were sent to the motors. Additionally, the rotation speed and orientation of the robot were determined with the MPU6050 IMU (Inertial Measurement Unit) sensor. To ensure that the robot reaches the determined targets, goal setting and reaching capabilities have been improved by using 2D nav goal. The ROS Move Base package implemented the motion planning and control of the robot.