Localization and State Estimation for Autonomous Driving in Urban Environments

Institut
Lehrstuhl für Fahrzeugtechnik
Typ
Bachelorarbeit / Semesterarbeit / Masterarbeit /
Inhalt
experimentell / theoretisch /  
Beschreibung

EDGAR, the new research vehicle for autonomous driving at TUM, is currently under construction. At the same time, an overall software stack is being developed that will enable fully autonomous driving in urban environments.

Within the scope of this thesis, a concept for state estimation and localization of the ego vehicle will be conceptualized, implemented and validated using real and simulation data. Different sensor data will be used (IMU, wheel speed, LiDAR, camera, etc.).

Open source algorithms will be evaluated, assessed and compared. Subsequently, a toolchain will be developed and implemented to enable the most precise localization and state estimation possible from the available sensor data.

The following work packages are included in the study work to be assigned:

  • Literature research on existing concepts in research and industry
  • Evaluation and classification of open source algorithms
  • Development of an algorithm for localization and state estimation
  • Adaptation to the sensor concept of the research vehicle EDGAR
  • Integration of the developed software into the overall software
  • Documentation and visualization of the results

What we offer:

  • A highly motivated team of research associates and students pursuing the common goal of full-stack autonomous driving
  • Work with state-of-the-art hardware: HiL simulator, research vehicle EDDIE, cloud compute power
  • Work with state-of-the-art software tooling: ROS2, Docker, CI/CD
  • Build industry-relevant knowledge and software engineering skills

 

Voraussetzungen
  • Highly motivated teamplayer
  • Motivation to familiarize yourself with new topics
  • Ideally programming experience (Python, C++, Git, ROS2)
  • Ideally previous knowledge in the field of autonomous driving or sensor technology
Verwendete Technologien
Git, C++, Python, ROS2, Docker
Tags
FTM Studienarbeit, FTM AV, FTM AV Perception, FTM Sauerbeck, FTM Informatik
Möglicher Beginn
sofort
Kontakt
Florian Sauerbeck, M.Sc.
Raum: MW 3508
Tel.: +49 89 289 15342
sauerbeckftm.mw.tum.de
Ausschreibung