Browsing by Author "Lidauer, Jaakob"

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  • Accuracy of lidar based simultaneous localization and mapping in rural environments
    (2021-08-23) Lidauer, Jaakob
     Sähkötekniikan korkeakoulu | Master's thesis
    Simultaneous localization and mapping (SLAM) algorithms have received much attention due to their capability of constructing globally consistent maps without external measurements. SLAM implementations are commonly evaluated in urban environments, which is why they can be expected to work accurately in urban environments. However, SLAM would have meaningful applications also in rural environments. Therefore, the aim of this thesis is to evaluate the accuracy of a SLAM algorithm (LIO-SAM), in rural environments, as well as evaluate the effect of different algorithmic configurations on the accuracy. The accuracy is evaluated by comparing the trajectory created by the SLAM algorithm to a reference trajectory measured using a commonly employed lidar mapping method that is based on the global navigation satellite system (GNSS) and inertial measurements (IMU). By using the reference trajectory, the relative and absolute accuracy is evaluated for each SLAM configuration and dataset. Additionally, rigid alignment errors to world coordinates and local consistency errors are evaluated. The datasets of this thesis are captured using a purpose-built capture device, consisting of a Velodyne VLP-32C lidar, a Pixhawk 4 autopilot, and a u-blox ZED-F9P GNSS receiver. The datasets are captured in rural and urban environments using an unmanned aerial vehicle and a car, as well as by foot. The results show that the obtained accuracy of SLAM depends on the SLAM configuration and on the environment. Contrary to the initial expectation, rural environments did not always have worse accuracies than urban environments. However, based on the results, the accuracy of LIO-SAM deteriorates in environments in which only few features are visible in the direction of travel (such as open fields and highways). For datasets captured in rural environments, the smallest obtained absolute errors (i.e., best accuracies) were: 0.14m RMSE and 0.23deg RMSE, and the smallest relative errors were: 0.04m RMSE and 0.07deg RMSE.
  • Power Line Tracking for UAVs Using Lidar
    (2018-12-19) Lidauer, Jaakob
     Sähkötekniikan korkeakoulu | Bachelor's thesis