Projects | Expert-based data analysis and quality processes
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AutoMap - Development of a robust positioning system for autonomous vehicles based on captured environmental information and GNSS/IMU dataDetermining the exact position of vehicles is not only crucial for autonomous driving, but also for many other applications. However, existing technologies, such as global navigation satellite systems (GNSS) or inertial measurement units (IMU), are reaching their limits due to interference and inaccuracies, especially in urban areas.Led by: Hamza Alkhatib, Sören VogelTeam:Year: 2023Funding: mFUND project | funded by the BMDV (Bundesministerium für Digitales und Verkehr)Duration: 2023-2025
© GIH
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Uncertainty Modeling for Kinematic LiDAR-based Multi-Sensor SystemsGoal of this PhD project is to investigate methods to enable a consistent estimation of uncertainties for LiDAR-based MSSs, while dealing with the challenges caused by the uncertainties of individual sensors and their interactions in the system.Led by: Prof. Dr.-Ing. Ingo NeumannTeam:Year: 2022Funding: DFG - GRK 2159 i.c.sensDuration: 11/2022 - 11/2025
© GIH | Dominik Ernst
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Development of a collaborative robust Particle Filter for State Estimation with Stochastic and Quantity-based Uncertainties in Sensor NetworksPrecise vehicle localization is a critical requirement for autonomous driving, especially in urban settings where GNSS signals often fail. To address this challenge, an advanced Particle Filter framework estimates vehicle pose by fusing 3D LiDAR data with complementary sensor inputs. The primary motivation is to achieve low-decimetre localisation accuracy despite the complexities of urban environments.Led by: PD Dr.-Ing. Hamza AlkahtibTeam:Year: 2022Funding: DFG - GRK 2159 i.c.sensDuration: 11/2022 - 11/2025