Continuous time trajectory estimation for 3D SLAM from an actuated 2D laser scanner
This thesis aims at estimating trajectories for 3D SLAM applications. A continuous time formulation allows solving multiple problems inherent to the traditional discrete time approaches seamlessly, such as sensor fusion of actuated 2D laser scanner data with inertial measurements. Special care is taken when choosing an appropriate trajectory representation. The well-known ICP algorithm used for rigid registration is extended significantly so it can deal with continuous-time, multi-view registration of deformable scans. The resulting algorithm can be employed online in a time-windowed fashion to get an open-loop trajectory estimate and offline for global optimization to further reduce the drift. In contrast to previous work we are able to provide ground truth data for evaluation by extending an existing simulator so that it can simulate actuated 2D laser scanner data with corresponding inertial measurements. Experiments on synthetic data with different scenarios, noise levels and parameter settings show the versatility, stability and adaptability of our algorithm as well as its high overall accuracy.