Performance of Different SLAM Algorithms for Indoor and Outdoor Mapping Applications

Abstract

Indoor and outdoor mapping studies can be completed relatively quickly, depending on the developments in Mobile Mapping Systems. Especially in indoor environments where high accuracy GNSS positions cannot be used, mapping studies can be carried out with SLAM algorithms. Although there are many different SLAM algorithms in the literature, each can produce results with different accuracy according to the mapped environment. In this study, 3D maps were produced with LOAM, A-LOAM, and HDL Graph SLAM algorithms in different environments such as long corridors, staircases, and outdoor environments, and the accuracies of the maps produced with different algorithms were compared. For this purpose, a mobile mapping platform using Velodyne VLP-16 LIDAR sensor was developed, and the odometer drift, which causes loss of accuracy in the data collected, was minimized by loop closure and plane detection methods. As a result of the tests, it was determined that the results of the LOAM algorithm were not as accurate as those of the A-LOAM and HDL Graph SLAM algorithms. Both indoor and outdoor environments and the A-LOAM results' accuracy were two times better than HDL Graph SLAM results.