<![CDATA[This article reviews an autonomous mobile robot with mecanum wheels using localization and mapping with Lidar. The mecanum wheeled robot is capable of autonomously moving from point A to point B. This study aims to determine the level of accuracy and precision in mapping to ensure the robot can operate efficiently, as well as to develop the ability to perform real-time environmental mapping using data obtained from the Lidar A2M12 sensor. It also aims to implement the SLAM (Simultaneous Localization and Mapping) algorithm to simultaneously determine the robot's position and orientation while mapping. For independent movement, the robot must be aware of its surroundings and its position within that environment. The method used is simultaneous localization and mapping using the RPLidar A2M12 sensor and ROS (Robot Operating System). Based on the testing results, the gmapping SLAM error rate is 3.34%, with a sensor distance and angle measurement error of 1.16%. Overall, this autonomous robot can be used even in open areas and with simple obstacles.]]>
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