PCDA™ SLAM-BASED TECHNOLOGY FOR POINT CLOUD AND TRAJECTORY OPTIMIZATION FOR AIRBORNE, LAND, AND INDOOR APPLICATIONS IN GNSS-DENIED ENVIRONMENTS
Keywords: Trimble Applanix PCDA TM, SLAM, GNSS, LiDAR point cloud data, trajectory data, check point RMS
Abstract. This paper presents the results of assessing the performance of Trimble Applanix PCDA™ SLAM-based technology to simultaneously optimize any mobile mapping system trajectory and LiDAR point cloud data in a GNSS-denied environment. The simultaneous use of inertially-aided GNSS data along with LiDAR point clouds to optimally correct shifts and/or drifts in the trajectory in GNSS-denied environments is addressed in detail in this paper. A number of Trimble MX50 Mobile Mapping System data sets were acquired in Germany particularly to assess the performance of PCDA™. The land mobile mapping data sets were acquired in deep urban canyons which were purposely acquired that way to reach the most challenging land mobile mapping data sets in a GNSS-denied environment. The PCDA™ technology assessment results are presented in detail. In summary, the results show how LiDAR data can successfully be used to correct the trajectory shifts and drifts due to GNSS outages by simultaneously optimizing both point cloud and trajectory data.