This project, titled RoboMapper: Autonomous Mapping Using ROS Hector SLAM with 2D-RPLiDAR in Gazebo and RViz Simulators focuses on the development of a robot capable of mapping indoor environments autonomously using Simultaneous Localization and Mapping (SLAM). The robot utilizes advanced sensor systems, including LiDAR, integrated with ROS (Robot Operating System) to navigate and generate real-time maps of its surroundings. This technology is particularly beneficial for indoor navigation in areas such as warehouses, offices, or large buildings, where GPS-based navigation systems are ineffective. The project implements Hector SLAM, a robust algorithm for indoor mapping, which helps the robot create precise 2D maps while localizing itself within the environment. The robot is designed with a focus on obstacle detection and path planning using algorithms like A* and DWA (Dynamic Window Approach) to ensure efficient navigation around both static and dynamic obstacles. Key features include real-time map generation, autonomous path planning. This project demonstrates how autonomous systems can be applied to simplify indoor navigation and enhance operational efficiency in indoor environments.