Georeferencing of Mobile Mapping Data

Abstract

One of the main tasks in Engineering Geodesy is the measurement and monitoring of geometry related phenomena on local or regional scales. Examples are the generation of high-resolution 3D city models, as they are needed for autonomous driving, and the monitoring of artificial or natural objects, such as bridges, glaciers or sliding slopes. In the last decade, these tasks have been more and more realized using mobile sensor platforms, such as robots, cars, or Unmanned Aerial Vehicles (UAVs). The platforms are equipped with laser scanners and cameras and collect data while moving through the environment. In this way, it is possible to perform the task of mapping an area of interest with a much higher density and efficiency. <br> A crucial part of this mobile mapping process is the georeferencing of the locally acquired sensor data, registering those data in a globally defined coordinate system. For this, it is necessary to know the vehicle's trajectory during the measurement process. This thesis introduces several contributions to the general field of trajectory estimation of moving platforms, including better sensor configurations, new calibration procedures and improved processing algorithms. Another set of contributions describes the development, calibration and evaluation of some specific mobile mapping systems. These are airborne and ground-based systems, with applications ranging from general surveying and deformation analysis to agriculture.