Student Thesis: Sensor Fusion and Localization for Autonomous Driving

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

For my research in the field of sensor fusion and localization for autonomous driving, I am always looking for motivated students.

You will be part of a team of researchers and other students and gain experience with modern industry standard software development tools.

If you feel like pushing the limits of autonomous driving and gathering valuable experience, write a short mail and we can set up a call and discuss interesting topics.

 

Student Projects can include following topics:

  • Sensor Fusion: lidar, camera, radar
  • Localization with different sensors
  • Environmetal perception
  • Percepttion and sensor simulation
  • Mapping and post-processing of generated maps

What we offer:

  • EDGAR: A Level 5 research vehicle to deploy your software
  • 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
  • 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, Unity
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