Simultaneous localization and mapping (SLAM) is a fundamental technique used in robotics, autonomous vehicles, and augmented reality to construct maps of unknown environments while simultaneously keeping track of the robot's location within that environment. SLAM is particularly significant for unmanned aerial vehicle quadrotors because it enables them to navigate autonomously in unknown or GPS-denied environments while simultaneously creating maps of their surroundings. Therefore, this paper presents the method to apply SLAM in a quadrotor in both simulation and experiment. With simulation, the quadrotor and mapping are presented in the Gazebo simulation. Besides, the experiment with a quadrotor model is used, and collected SLAM information which is sent to an unmanned ground vehicle to improve the performance of the system.