Fast planar surface 3D SLAM using LIDAR

• Published in: Robotics and autonomous systems 2017-06, Vol.92, p.197-220
• Main Authors: Lenac, Kruno, Kitanov, Andrej, Cupec, Robert, Petrović, Ivan
• Format: Article
• Language: English
• Subjects: ESDS filter; Mapping; Planar map; Planar surface registration; Point cloud segmentation; Pose estimation
• ISSN: 0921-8890; 1872-793X
• DOI: 10.1016/j.robot.2017.03.013

In this paper we propose a fast 3D pose based SLAM system that estimates a vehicle’s trajectory by registering sets of planar surface segments, extracted from 360∘ field of view (FOV) point clouds provided by a 3D LIDAR. Full FOV and planar representation of the map gives the proposed SLAM system the capability to map large-scale environments while maintaining fast execution time. For efficient point cloud processing we apply image-based techniques to project it to three two-dimensional images. The SLAM backend is based on Exactly Sparse Delayed State Filter as a non-iterative way of updating the pose graph and exploiting sparsity of the SLAM information matrix. Finally, our SLAM system enables reconstruction of the global map by merging the local planar surface segments in a highly efficient way. The proposed point cloud segmentation and registration method was tested and compared with the several state-of-the-art methods on two publicly available datasets. Complete SLAM system was also tested in one indoor and one outdoor experiment. The indoor experiment was conducted using a research mobile robot Husky A200 to map our university building and the outdoor experiment was performed on the publicly available dataset provided by the Ford Motor Company, in which a car equipped with a 3D LIDAR was driven in the downtown Dearborn Michigan. •Efficient processing of 3D point clouds achieved by projecting them onto image planes.•Performing fast segmentation of projected point clouds into planar segments.•Exploiting the sparsity of SLAM information matrix without approximation error.•Technique that combines planar segments that lie on the same plane into one plane.