Research on ROS-based SLAM Implementation for Indoor Environments

Simultaneous localization and mapping (SLAM) is applicable in robotics and mobile platforms. SLAM approaches empower robots to create intricate maps of their surroundings while concurrently pinpointing their exact location within the dynamic environment in real-time. SLAM approaches differs from general robotics in that they lack a dependable source of odometry, requiring them to adapt to the unpredictable movements of mobile devices. We proposed the use of SLAM approaches in indoor environments in the robot operating system (ROS). The ROS encompasses a range of open-source software libraries and tools. These resources not only support the research discussed in this article but also facilitate the development of robot applications. In ROS, the libraries were selected for developing and integrating diverse robotic components, including sensors, hardware, and algorithms. SLAM approaches with the libraries allows for various visualization and simulation tools, making it an ideal platform for conducting SLAM research and implementation.