Nowadays, with the developing technology, the need for manpower has decreased and the machines have been able to do almost anything. In this way, time is also achieved and error rates have become quite low. Architecture is also seen as a space where the need for the architect is reduced. The fact that artificial intelligence can make architectural design has opened up different fields of application especially in the field of interior architecture. Now, mobile applications can be downloaded and we can easily design a space. However, when architects want to redesign the design of a space, they must first take the dimensions of the space in detail. After drawing out the draft plans, they clear these plans and then make drawings on the computer. In this article, it is investigated how a long process can be done in a faster and more practical way in order to facilitate the work of architects.

On the other hand, simultaneous localization and mapping is an important problem for autonomous mobile robots. Mapping a closed environment requires the system to be positioned at the same time. Positioning in open environments is ensured by GPS and reliable results are obtained. In closed environments, reliable results cannot be obtained since GPS signals cannot be received in sufficient amounts. Several methods have been used to solve this problem. Positioning can be made by many methods such as Odometry, Iterative Closest Point, Adaptive Monte Carlo Localization or EKF filters methods [1-2]. Working with 3-D laser scanning technique, the rays coming out of the tower hit the obstacle periodically and go back. As the speed of light and the turnaround time of the beam are known, the distance between the LIDAR and the obstacle is easily determined. Through this beam sent in the form of a point cloud, each point of the obstacle is detected and the obstacle distance is determined. LIDAR is preferred for mapping operations due to the ease of measurement of the distance to LIDAR in closed environments. There are also studies using various sensors such as RGB-D, Sonar, Radar, but LIDAR is preferred for reliability [3].