Advanced Robotics / Deep Learning for Robotics
Organizational issues
| Term: | summer semester (2/1/0/4) |
| Requirements: | Fundamentals of robotics |
| Exam: | oral |
| Lecturer: | Prof. Dr.-Ing. Ulrike Thomas |
| Sign up Deep Learning for Robotics: | >>> OPAL |
| Sign up Lab: | >>> OPAL |
| Timetable: | Link to the timetable of the TU |
| Practical course |
In the practical part of the course, students learn about and apply different reinforcement learning methods in several experiments. At the end of the practical course, a robot manipulation task is solved using these methods. |
Contents
The content of the lectures will be robot learning, locomotion and intelligent systems. It is a one semester course combined with practical course work. The focus is on learning algorithms for robotics.
Outline:
- Machine Learning for robotics
- Bayes Filters in robotics
- Reinforcement Learning
- Deep Learning
- Learning how to graps
- Learning how to walk
