Autonomous Mobile Robot Localization and Mapping for Unknown Construction Environments

Abstract

With the rapid advancement of laser scanning and photogrammetry technologies, geometric data collection at construction sites by contractors has been increased to improve constructability, productivity, and onsite safety. Especially, the latest laser scanning technology provides faster scanning-speed, longer ranges, and higher accuracy and resolutions. However, the conventional static laser scanning method suffers from operational limitations due to the presence of many occlusions commonly found in a typical construction site. Full scanning without information loss requires that the scanning location should be changed several times, which also leads to extra work for registering each scanned point cloud. Alternatively, this paper presents an autonomous mobile robot which navigates a construction site and continuously updates a progress of 3D scanning with point clouds. This mobile robot system uses the 3D simultaneous localization and mapping (SLAM) technique to determine its navigation paths in an unknown environment, capture the survey-quality RGB mapped point cloud data, and automatically register the scans for geometric reconstruction of a construction site. The performance of the overall system was tested in indoor environments and validated with promising results.