This study investigates the feasibility of a mobile robot navigating and discovering its location in unknown environments, followed by the creation of maps of these navigated environments for future use. First, a real mobile robot named TurtleBot3 Burger was used to achieve the simultaneous localization and mapping (SLAM) technique for a complex environment with 12 obstacles of different sizes based on the Rviz library, which is built on the robot operating system (ROS) booted in Linux. It is possible to control the robot and perform this process remotely by using an Amazon Elastic Compute Cloud (Amazon EC2) instance service. Then, the map to the Amazon Simple Storage Service (Amazon S3) cloud was uploaded. This provides a database to display maps and use them at any time for navigation without the need to redraw the map. This map can be accessed by using an authentication process (username and password) supervised by the cloud server administrator. After that, using the serverless image handler (SIH), with the aid of this solution, you can change the size of images, change the color of the background, format them, or add watermarks. Experiment results demonstrated the ability to build a map of an unknown location in a complex environment and use it for navigation tasks on a real mobile robot via remote control. It also showed the success of the process of storing the map for future use and the process of modifying the map using SIH.