Simultaneous Localization and Mapping (SLAM) algorithms provide a robust solution for mobile robots localization and map building of surrounding environment even when most used positioning systems (GPS) are not available for autonomous navigation, such as in indoor or subterranean locations. Being able to set a team of robots to resolve this common task and enable it to collaborate, it is possible to obtain better results in shorter time. In this thesis work, carried out in collaboration with LINKS Foundation, a fully distributed collaborative SLAM system, based on lidar sensor data processing, has been designed and partially developed exploiting the ROS2 open-source framework.