Ursprungligen ett examensarbete från NTNU 2017

Development of Mobile Mapping System (MMS) began in the late 1980s and is constantly growing. Thanks to continuous developments in both scanning and positioning technologies, Mobile Mapping Systems are gaining more and more importance in many applications. Different solutions are available on the market with different technical specifications. Terrestrial MMS technology goes back to the 90's when the first experiments showed the potential of mobile mapping for GIS applications. Ultimately, this gave birth to commercial operating systems used for example for 3D mapping of road, railways, city and coastal areas. There are, nowadays, different commercial MMS technologies, showing the best example of sensor integration for optimal acquisition of 3D georeferenced spatial data. One example is the Optech Lynx Mobile Mapping System operated by TerraTec. The georeferencing of data from the remote sensing system, e.g. a laser point cloud, is based on the position and orientation of the platform of the Mobile Mapping System. The navigation sensors collect data about the platform's position and orientation. A Kalman filter can be used to utilize this information and estimate a trajectory of the platform. The trajectory is the path described by the platform's movements in space. The estimation of the trajectory based on the sensor data works well and can give results with an accuracy of a few centimetres in areas with GNSS signals from multiple satellites. In areas with high buildings, trees or other obstacles, the loss of GNSS signals can, however, lead to an accuracy of the trajectory that is significantly worse. In large mobile mapping projects, there are high demands on both accuracy of the data and efficiency in data collection and processing. Estimation of trajectory is performed using a well-known problem in robotic mapping called “Simultaneous Localization And Mapping (SLAM)”. SLAM is the problem of creating a map of an unknown environment at the same time as positioning the trajectory in this environment. The purpose of this thesis is to investigate the efficiency of SLAM in the post-processing of mobile mapping data. The thesis should contain a description of the theory of mobile mapping systems, including the hardware and software packages used. As a result of the thesis, based on the collected data in the field, the student should comment on the achievable accuracy improvement by introducing SLAM in the post-processing of mobile mapping data.