Real-time Simultaneous Navigation and Mapping (SLAM)

Laser scanned point clouds are relevant for geometric analysis, building maintenance and energy modeling, yet obtaining fully registered point clouds is a labor-intensive process when targets or common registration features are absent. Thus, we propose a versatile mobile platform that forms an incremental 3D map of the environment in real time using an orthogonal pair of LIDAR (Light Detection and Ranging) devices. The horizontal scanner aims to estimate the robot position and orientation with SLAM (Simultaneous Localization and Mapping) techniques whereas the vertical scanner recovers the building structure in the vertical plane. We also developed a real time point cloud visualization tool that allows an operator to track the mapping progress. The method was evaluated with walk-through laser scans of a complete building floor.
 

Publications:

Chen, J. and Cho, Y. (2016). “Real-time 3D Mobile Mapping for the Built Environment.” International Symposium on Automation and Robotics in Construction (ISARC), Auburn, AL, July 18-21, 2016.