The Doctoral School in Science and Engineering is happy to invite you to Meisam KABIRI’s defence entitled
5G-Enhanced Indoor UAV Localization and SLAM Through Sensor Fusion
Supervisor: Prof Holger VOOS
Indoor localization and navigation for Unmanned Aerial Vehicles (UAVs) remains challenging due to GPS denial and the limitations of traditional visual-inertial systems. The emergence of 5G networks offers new opportunities for precise indoor positioning, but their integration with existing UAV navigation systems remains unexplored. This thesis systematically investigates the feasibility of integrating 5G Time-of-Arrival (ToA) measurements with advanced sensor fusion techniques to enhance indoor localization and SLAM (Simultaneous Localization and Mapping). Two approaches are proposed for localization: a real-time Error State Kalman Filter (ESKF) framework and a Pose Graph Optimization (PGO) method. The study leverages the EuRoC MAV dataset, augmented with simulated 5G ToA measurements, to evaluate system performance across diverse indoor scenarios and 5G base station densities. Using just IMU and ToA measurements as a minimal sensor setup, both proposed methods demonstrate significant improvements in pose estimation accuracy and drift reduction
Additionally, a unified SLAM framework is developed to incorporate 5G ToA measurements alongside visual-inertial data. This integration provides three crucial advantages: global localization and mapping, resolution of scale ambiguity inherent in monocular SLAM, and enhanced system resilience in challenging conditions where traditional visual-inertial methods may fail. Building on visual-inertial datasets collected in Aerolab augmented with simulated 5G ToA measurements, the results demonstrate that this integration significantly enhances navigation capabilities, particularly in minimal sensor configurations. This research bridges the gap between visual-inertial and 5G radio-frequency-based approaches, establishing realistic baselines for understanding the practical impact of 5G technology on robotic localization and navigation.