Learning Robots
At the beginning of the project, the range of contents that should be covered in the project will be discussed in detail and the relevant methods will be identified. This is accompanied by a literature search, reading, and discussion phase. In this phase relevant mathematical and computational methods will be selected and discussed. In the second phase, the team starts to implement the experimental design on a simulated robot. Regular team meetings and supervisory consultations lead to an iterated improvement of the software. In the third phase, the thoroughly tested software will be transferred to the robot and tested in a real or simulated environment. The results are written up in a final project report and are presented in a final project presentation.
Sprache: englisch
Contents of the course
(90 LP/ECTS) — Berufsbegleitendes Weiterbildungsstudium
The study program combines self-study and group work in a flexible online learning environment. Students have access to video lectures, a detailed and user-friendly script tailored for working professionals, as well as interactive quizzes and exercises. Regular tutorial sessions and online office hours with mentors support the learning process, while discussion forums facilitate exchange among students. For more detailed information, please refer to the module handbook.
Programming in Python or C++, basics of ROS and simulation environments, understanding of machine learning concepts (e.g. Neural Nets, Reinforcement Learning, Computer Vision) may be helpful.
