<![CDATA[Omnidirectional mobile robots require reliable navigation and mapping capabilities to operate in unknown environments. This study aims to design and implement a three-wheeled omnidirectional robot with a control system based on the Robot Operating System (ROS) and a LiDAR sensor, utilizing the GMapping algorithm for 2D mapping. The Frontier Cells Detection algorithm is employed to identify unmapped areas, while the A* algorithm is implemented for path planning toward those areas. The navigation system is equipped with odometry and kinematics to estimate the robot’s position in real-time. Testing was conducted in various room shapes, both with and without obstacles, across 10 trial runs. The results show that the system is capable of producing accurate maps, with an average mapping error ranging from 0.22% to 1.72% in obstacle-free environments, and up to 4.86% in environments with obstacles. The highest recorded error was 8.29%. These results indicate that the integration of the applied navigation and mapping algorithms is effective in supporting the mobility and exploration capabilities of the robot in indoor environments.]]>
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