In the context of the rapid development in the field mobile robotics and the increasing integration of autonomous systems into industrial processes, orthophoto mosaicking emerges as an important area with vast potential applications. Traditional methods relying on expensive LiDAR sensors, dedicated autonomous drones, and similar technologies make this process relatively inaccessible. This paper explores an innovative approach to orthophoto mosaicking of outdoor environments, emphasizing accessibility, the use of relatively affordable RGB-D sensors, and real-time orthophoto mosaic generation. By integrating RGB-D cameras, specifically the Intel RealSense D455, into the ROS2 environment, the RTAB-Map SLAM approach is employed to generate a 3D map of the environment, which is then transformed into an orthophoto mosaic. The system designed in this way is intended for autonomous robots that already use the aforementioned sensors and tools to perform other tasks in the environment that they can map at the same time. The paper presents the theory behind orthophoto mosaicking, the operation of RGB-D cameras, and the detailed system implementation, along with conducted experiments and a qualitative analysis of results. Despite the perceived imperfections of the presented solution in its initial form, this paper serves as a solid foundation for further research and the development of innovative approaches to orthophoto mosaicking, contributing to the growing need for efficient and accessible solutions in industrial contexts.