This paper presents a method of 3D maps integration based on overlapping regions detection and matching.
 The algorithm works without an initial guess about transformation. The process of finding transformation between maps can be divided into two steps.
 The first one is the estimation of an initial transformation based on feature extraction, description, and matching.
 The assumption is that the maps have an overlapping area that can be used during feature based processing.
 Then the found initial solution is corrected using local methods, for example, Iterative Closest Point (ICP) algorithm.
 The maps are stored in the octree based representation (octomaps) but during transformation
 estimation, a point cloud representation is used as well. In addition, the presented method was verified in various experiments: in a simulation, with wheeled robots, and with publicly available datasets.
 Eventually, the solution can be applied to many robotic applications related to the exploration of unknown environments.
 Nevertheless, so far the implemented method was validated with a group of wheeled robots.