AULA-KI: Adaptive Umgebungsabhängige Lokalisierung von autonomen Fahrzeugen durch Methoden der künstlichen Intelligenz
The project aims to create the foundation towards a new AI-group composed of researches at the OvGU and the ifak e.V. focussing on developing, extending and applying AI-Methods for industrial scenarios. This first project aims to solve the problem of degraded sensor quality in autonomous cars in harsh weather conditions. To this end, methods will be developed to detect these weather events, communicate them to specialized decision components and mitigate them. This will provide means towards a more robust localization information and thus more robust behavior of autonomous cars.
| Start | 01.October 2022 |
| End | 30.September 2025 |
| Volume | 950k € |
| Leader | Dr.-Ing. Christoph Steup |
Members:
- Dominik Weikert M.Sc
- Adrian Köring M.Sc
Partners:
Associate Partners:
Materials
Slide-Show for possible cooperation partners for follow-up projects (German)
Master/Bachelor Thesis
Phillip Rittweger - Entwicklung einer Mixed-Reality Integration für ein autonomes
Personenshuttle zur Erprobung des Flottenbetriebs
Publikationen
- Adrian Köring and Christoph Steup
- PyramidEnsemble: Joining Large and Small Models
- 2023 IEEE Symposium Series on Computational Intelligence (SSCI), Mexico City, Mexico, 2023, pp. 689-694, doi: 10.1109/SSCI52147.2023.10371902.
- Dominik Weikert, Christoph Steup, Sanaz Mostaghim
- Adverse Weather Benchmark Dataset for LiDAR-based 3D Object Recognition and Segmentation in Autonomous Driving
- 2024 IEEE Conference on Artificial Intelligence (CAI), Singapore, Singapore, 2024, pp. 125-126, doi: 10.1109/CAI59869.2024.00031, -> pdf ©2024 IEEE
