Autonomous vehicles can be about cars, trucks, drones, or different types of special vehicles, such as mobile robots. The development of autonomous vehicles can lead to changes in several industries in the not so distant future. An autonomous vehicle is equipped with built-in processors and sensors that can detect the environment, perform sensor fusion for decision making, and have continuous control and steering. The course provides an in-depth introduction to autonomous vehicles where both Artificial Intelligence (AI) algorithms and their system aspects are studied.
The course consists of both theoretical and experimental elements, and is closely related to current research and development. The topics covered include: key concepts of the perception-planning-control pipeline for autonomous driving (AD); key concepts of machine learning (ML), especially reinforcement learning (RL), and deep reinforcement learning (DRL);hands-on exercises with one of the popular open-source ML frameworks such as Tensorflow or PyTorch; Training, deployment and validation ML-based autonomous driving algorithmsin a simulation environment.
Algorithms and Systems for Autonomous Vehicles, 7.5 credits
Autumn Term 2024
The information below is only for exchange students
Starts
1 November 2024
Ends
19 January 2025
Study location
Varied
Language
English
Type of studies
Mixed,
50%,
Distance
Number of mandatory meetings
No mandatory meetings.
Number of other meetings
None
Required Knowledge
Admission to the course requires 90 CREDITS of previous studies including courses in the field of Artificial Intelligence or Machine Learning of at least 7.5 Credits.
Selection
Students applying for courses within a double degree exchange agreement, within the departments own agreements will be given first priority. Then will - in turn - candidates within the departments own agreements, faculty agreements, central exchange agreements and other departmental agreements be selected.
Application code
UMU-A5420
Application
This application round is only intended for nominated exchange students. Information about deadlines can be found in the e-mail instruction that nominated students receive.
The application period is closed.
