Picture of Gerald Würsching

Gerald Würsching, M.Sc.

Technical University of Munich

Informatics 6 - Associate Professorship of Cyber Physical Systems (Prof. Althoff)

Postal address

Postal:
Boltzmannstr. 3
85748 Garching b. München


Curriculum Vitae

Gerald Würsching joined the Cyber Physical Systems Group as a research assistant and PhD student under the supervision of Prof. Dr.-Ing. Matthias Althoff in 2020. He recieved his Bachelor of Science and Master of Science degrees in mechanical engineering from the Technical University of Munich in 2017 and 2020, respectively. His research interests include safe motion planning for autonomous vehicles.


Offered Thesis Topics

I am always looking for self-motivated students to solve interesting problems arising in my research areas. If you are interested in one of the currently available topics, simply send me an e-mail with your up-to-date CV and transcript of records attached.

Students from Informatics, Mechanical Engineering and Electrical Engineering are welcome to apply.

Currently available:

-

Ongoing:

  • [MA] - Motion Planning for Autonomous Vehicles Using Rapidly Exploring Random Trees and Reachable Sets
  • [MA] - Specification-compliant Maneuver Extraction from Reachability Analysis of Automated Vehicles
  • [MA] - Cooperative Motion Planning for Automated Vehicles using Reachable Sets

Teaching

SS21

Exercise: Gems of Informatics 2

Seminar: Cyber Physical Systems

Practical Course: Motion Planning for Autonomous Vehicles

WS21/22

Exercise: Techniques in Artificial Intelligence

Seminar: Cyber Physical Systems

Practical Course: Motion Planning for Autonomous Vehicles


Publications

2021

  • Würsching, Gerald; Althoff, Matthias: Sampling-Based Optimal Trajectory Generation for Autonomous Vehicles Using Reachable Sets. IEEE International Conference on Intelligent Transportation Systems (ITSC), 2021 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
  • Ye, Egon; Würsching, Gerald; Steyer, Sascha; Althoff, Matthias: Offline Dynamic Grid Generation for Automotive Environment Perception Using Temporal Inference Methods. IEEE Robotics and Automation Letters, 2021 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)