Leibniz Universität Hannover Faculty Faculty of Civil Engineering and Geodetic Science
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Geodetic Institute
 
Geodetic Institute Hanover Teaching Theses

Master's theses at the Geodetic Institute

Open master's theses

  • ESRI Parcel Fabric for parcel management – a field comparison
    This thesis (bachelor's or master's) conducts a detailed literature review on the topic of LADM (Land Administrative Domain Model) and identifies and analyses successful case studies worldwide (max. 3-4 case studies). This involves a qualitative comparison of the approaches in the case studies in order to identify success factors for the successful implementation of a LADM in the form of ESRI Parcel Fabric software in the case studies.
    Led by: PD Dr.-Ing. Hamza Alkhatib, Dr.-Ing. Jörn Bannert
    Year: 2026
    Duration: from 10/2025
    © Image source: ESRI Parcel Fabric
  • Concept Studies for a Field Check Procedure for Kinematic LiDAR-based MSS
    Kinematic Mobile Mapping Systems (MSS) are used to efficiently capture areas like roads and industrial sites, thanks to advanced sensors and data processing algorithms. Despite the efficiency, the complexity of processing makes it difficult for users to fully evaluate results. Errors in calibration or sensor issues can cause deviations in point clouds that are hard to detect. This thesis aims to develop a field check procedure to assess if a LiDAR-based MSS meets its specifications. The procedure will be developed through simulations that introduce systematic deviations and should be easy to execute without needing reference data. The evaluation focuses on the captured point cloud, and the field check will define necessary conditions to verify system performance. The project requires skills in Python or MATLAB.
    Led by: PD Dr.-Ing. Hamza Alkhatib; Dominik Ernst M. Sc.
    Year: 2026
    Duration: from the summer semester of 2026
    © GIH
  • A Robust LiDAR Perception Pipeline for Static and Dynamic Object Detection on a Quadruped Robot
    Autonomous robots need reliable environmental perception for safe operation, often using LiDAR sensors to produce 3D point clouds. Distinguishing static from dynamic objects is crucial for collision avoidance and path planning. Quadruped robots, valued for their terrain adaptability, often use low-cost LiDAR sensors, which can be noisy and produce lower-density data, complicating perception further due to movement-induced noise. This thesis aims to create a robust perception pipeline to detect objects using data from a Unitree 4D L1 LiDAR on a Unitree B1 quadruped robot. The approach involves reviewing existing detection methods, designing a detection pipeline, and evaluating its accuracy, noise robustness, and efficiency. Skills in Python or MATLAB are required.
    Led by: PD Dr.-Ing Hamza Alkhatib, Dr.-Ing. Rozhin Moftizadeh
    Year: 2026
    Duration: from 11/2025
    © GIH
  • Development and Quality Assurance of a rotating Sensor Tower based on two Cost-effective Unitree 4D LiDAR L2 devices for Complete Environment Detection with Bias Estimation Routine in Unknown Environments
    Over the past decade, LiDAR sensors have become significantly more affordable, allowing their integration into everyday devices, such as robot vacuums. Volumetric LiDAR sensors, like the Unilidar 4D LiDAR L2 with an integrated 6DOF IMU, now cost under €1,000 and offer a field of view of 360°x96°. By using two sensors positioned oppositely, a complete 360°x360° field of view can be achieved. Mounting these sensors on a motorized rotating base can further refine bias estimation in unknown environments.
    Led by: Christian Hartberger, M. Sc.
    Year: 2026
    Duration: from 04/2026
    : Design concept for the universal LiDAR-based sensor tower : Design concept for the universal LiDAR-based sensor tower © GIH
  • Integrating Measurement Uncertainty for Enhanced Reliability in Digital Bathymetric Models
    Nowadays mapping of underwater topography has been greatly facilitated by high-resolution systems such as multibeam echosounders (MBES). Nevertheless, the extensive data collected by these instruments are often contaminated with varying degrees of errors. This calls for caution in constructing Digital Bathymetric Models (DBMs), particularly for critical applications like waterway navigation. This master thesis aims to explore and enhance the quality of DBMs by incorporating measurement uncertainties systematically into the modeling process.
    Led by: PD Dr.-Ing. Hamza Alkhatib, Bahareh Mohammadivojdan, M. Sc.
    Year: 2025
    © GIH
  • Bayesian Deep Learning for Distribution Prediction of TLS Uncertainties
    In modern geodetic applications, Terrestrial Laser Scanning (TLS) is a key technology for the acquisition of detailed 3D information. While TLS has demonstrated remarkable capabilities, the need for robust uncertainty modelling is becoming increasingly apparent in critical applications such as deformation analysis. An accurate understanding and quantification of systematic deviations in TLS measurements is essential to ensure the reliability of 3D data. This research seeks to address this aspect by investigating the uncertainties within TLS data, in particular the systematic deviation in distance measurement.
    Led by: PD Dr.-Ing. Hamza Alkhatib, Jan Hartmann, M. Sc.
    Year: 2025
    © GIH
  • Real World Operational State Estimator for Autonomous Vehicles Based on LoD2 Maps
    The objective of this Master’s thesis is to incorporate real sensor data to further develop an existing simulation-based state estimation scheme. The main aims are: Investigate the limitations of the previously developed algorithm when paired with real data, Develop pre-processing algorithms that alleviate these limitations, Suggest necessary additions or modifications to the existing Multi Sensor System (MSS), and Assess the real-time capabilities of the newly developed scheme.
    Led by: PD Dr.-Ing Hamza Alkhatib, Mohamad Wahbah, M.Sc
    Year: 2025
    © GIH

Last Change: 27.10.25 Print

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