Arbeitsgruppe: Data Fusion

Teaching


Detailed information about the courses is available at Stud.IP.

Winter Term 2024/25

Mobile Robotics
Lecture + Exercise M.Sc. Link
The course is concerned with fundamental principles and algorithms for mobile robot navigation and perception. Topics are, for example, the locomotion of wheeled mobile robots, inertial sensors and beam-based sensors, probabilistic state estimation methods such as Kalman filters and sequential Monte Carlo methods (particle filters) for navigation and perception, Simultaneous Localization and Mapping (SLAM), and basic planning algorithms.
Seminar Perception for Autonomous Vehicles
Seminar M.Sc., B.Sc. Link
The seminar considers emerging technologies and methods for the perception of autonomous vehicles. It consists of a written scientific report and an oral presentation about a specific topic.
Practical Course Data Fusion
Practical Course M.Sc., B.Sc. Link
In this practical course, the students implement (sensor) data fusion algorithms and apply them to real-world problems in the context of mobile robotics, navigation, perception and tracking. Typical projects involve mobile robots such as drones and wheeled vehicles and sensors such as lidar, radar, cameras or inertial measurement units.

Summer Term 2024

Sensordatenverarbeitung
Vorlesung und Übung B.Sc. Link
Die Lehrveranstaltung vermittelt die grundlegenden Konzepte von Sensorsystemen sowie Algorithmen für die Sensordaten- und Signalverarbeitung.
Sensor Data Fusion
Lecture + Exercise M.Sc. Link
The course is concerned with fundamental principles and algorithms for sensor data fusion, i.e., the combination of noisy data in order to gain information.
Seminar Perception for Autonomous Vehicles
Seminar M.Sc., B.Sc. Link
The seminar considers emerging technologies and methods for the perception of autonomous vehicles. It consists of a written scientific report and an oral presentation about a specific topic.
Practical Course Data Fusion
Practical Course M.Sc., B.Sc. Link
In this practical course, the students implement (sensor) data fusion algorithms and apply them to real-world problems in the context of mobile robotics, navigation, perception and tracking. Typical projects involve mobile robots such as drones and wheeled vehicles and sensors such as lidar, radar, cameras or inertial measurement units.
Oberseminar Data Fusion
Seminar PhD, M.Sc, B.Sc. Link