Julian Dahlmann, M.Sc.
Julian Dahlmann, M.Sc.
Research Interests
- Global path planning
- Automated maneuvering of vehicle-trailer combinations
Biography
- Since November 2019 research associate at the Chair of Control Engineering, FAU Erlangen-Nuremberg, Germany
- 2017-2019 Study of electrical engineering (M.Sc.), FAU Erlangen-Nuremberg
- 2014-2017 Study of electrical engineering (B.Eng.), DHBW Ravensburg Campus Friedrichshafen
Publications
2022
- Dahlmann, J., Volz, A., Szabo, T., & Graichen, K. (2022). A Numerical Approach for Solving the Inversion Problem for n-Trailer Systems. In Proceedings of the American Control Conference (pp. 2018-2024). Atlanta, GA, USA: Institute of Electrical and Electronics Engineers Inc..
- Dahlmann, J., Völz, A., Szabo, T., & Graichen, K. (2022). A numerical approach for solving the inversion problem for general n-trailer systems. In Proceedings 2022 American Control Conference (ACC) (pp. 2018-2024). Atlanta, GA (USA).
- Dahlmann, J., Völz, A., Szabo, T., & Graichen, K. (2022). Trajectory optimization for truck-trailer systems based on predictive path-following control. In Proceedings of the 6th IEEE Conference on Control Technology and Applications (CCTA). Trieste (Italy).
Apprenticeships
- Internship supervision RT1 WiSe19/20
- Tutorial on Digital Control SoSe20
- Tutorial on Control Theory A WiSe20/21
- Tutorial on Digital Control SoSe21
- Tutorial on Control Theory A WiSe21/22
- Internship supervision RT1 SoSe22
Open theses
- Analysis and Compensation of Inaccuracies in a Slip-capable Vehicle Model
- Betreuung: Praktikum Regelungstechnik 1
Current and completed theses
- Betreuung: Praktikum Regelungstechnik 1
- Localization of mobile robots in unknown environments
- Global path planning for truck and trailer systems using tree search methods
- Distortion-free projection of scenarios for automated maneuvering systems
- Heuristic path parameterization using neural networks
- Development of a graphical user interface for planning maneuvers
- Camera-based object tracking for mobile robots
- Approximation of admissible trajectories for non-differentially flat vehicle combinations
- Parameter identification based on Bayesian optimization
- Control of a multi-tank test