Process of point clouds merging for mapping of a robot’s working environment

Abstract

The lidar is nowadays increasingly used in many robotic applications. Nevertheless the 3D lidars are still very expensive and their use on small robots is not economical. This article briefly introduces a construction of cheap 3D lidar for indoor usage based on the 2D laser range finder. Subsequently, this article introduces process of merging acquired point clouds. The every pair of neighboring point clouds is oriented in space to fit together in the best possible way. The result of this process is a 3D map of the robot working environment. This map can be segmented and further used for a navigation. In this way, it is also possible to map inaccessible and dangerous areas.