Simultaneous localization and mapping with Poisson's surface reconstruction

In a robotics or automation context, simultaneous localization and mapping are frequently employed. To continue using the system, the operator or user must be aware of the system's location in an unknown environment as well as the map or other features of that environment. Unmanned aerial vehicles are frequently employed in mapping disaster zones, fighting fires, performing maritime rescues, and many other tasks. To keep the operators aware of the present situation, the majority of these call for mapping and localization. Aerial mapping is required in order to collect data and continue operations with UAVs. SLAM can even be used indoors as long as an image can be captured in the environment. Landmarks, digital representation of the area, and the gathering of data are all possible with SLAM. This paper combines visual SLAM and gets the 3D point clouds. With these point clouds, for visualization, Poisson surface reconstruction is used.