Point-Cloud Mapping and Merging Using Mobile Laser Scanner

This paper presents a method for building a 3D point-cloud map in a residential environment using a mobile laser scanner. Several submaps are generated in different small areas using normal distributions transform (NDT) scan matching based simultaneous localization and mapping (SLAM) and full graph-based SLAM. When a loop closure (revisit) of the vehicle is detected, two constraints are used in the graph-based SLAM to improve submap accuracy: the poses of the vehicle obtained by NDT scan matching and one-to-one matching of pole-like landmarks, such as utility poles and traffic sign poles. The merging of the submaps is also performed using the full graph-based SLAM. The experimental results for three-submap generation and merging in a residential environment validate the effectiveness of the proposed method.