Improving Navigation with LiDAR Scanners: A Concept Study on the Use of Point Cloud Registration to Enhance and Evaluate Absolute Accuracy
Master thesis
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https://hdl.handle.net/11250/3078671Utgivelsesdato
2023Metadata
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- Master's theses (RealTek) [1724]
Sammendrag
This thesis is written as a collaboration with the Norwegian Mapping Authorities,with the aim of improving a navigation solution for a mobile mapping vehicle, based on data from a LiDAR scanner. A navigation system often consists of several differentsensors, like GNSS receivers, Inertial Measurement Units, and an odometer. However,these sensors do not always give flawless observations. Therefore, other sensors can benecessary to contribute to the overall performance.
The thesis aims to explore the use of Point Cloud Registration algorithms to align ageoreferenced point cloud with a raw LiDAR point cloud, and further use the predictedpoints to establish a quality measure of the navigation solution of the vehicle. Theprogram made to solve the problems is based on the Iterative Closest Points algorithmand is implemented to work on point clouds with absolute coordinates.
The results show that aligning point clouds using Point Cloud Registrationalgorithms will increase the absolute accuracy of a navigation solution with pooraccuracy. However, this alignment is not optimised for real-time use cases. A Kalmanfilter must be used to combine the result from the alignment with the other sensors,and be optimised for speed, in order to establish a fully operative navigation solution.
Using the program to establish a quality measure for a navigation solution has shownto be a viable option if the absolute accuracy is unknown, as the model manages todifferentiate between a higher and lower absolute accuracy. This could be beneficialto explore further, since quality control of navigation solutions from mobile mapping projects will, as a result, be a quality control of the delivered project itself.