Event
Cognitive Automobiles and Robots [SS232513500]
Lecturers
Organisation
- Angewandte Technisch-Kognitive Systeme
Part of
- Brick Seminar in Informatics (Bachelor) | Industrial Engineering and Management (B.Sc.)
- Brick Seminar in Informatics B (Master) | Industrial Engineering and Management (M.Sc.)
- Brick Seminar in Informatics A (Master) | Industrial Engineering and Management (M.Sc.)
- Brick Seminar in Informatics (Bachelor) | Economics Engineering (B.Sc.)
- Brick Seminar in Informatics B (Master) | Economics Engineering (M.Sc.)
- Brick Seminar in Informatics A (Master) | Economics Engineering (M.Sc.)
- Brick Seminar in Informatics (Bachelor) | Digital Economics (B.Sc.)
- Brick Seminar in Informatics B (Master) | Digital Economics (M.Sc.)
- Brick Seminar in Informatics A (Master) | Digital Economics (M.Sc.)
- Brick Seminar in Informatics (Bachelor) | Information Systems (B.Sc.)
- Brick Seminar in Informatics B (Master) | Information Systems (M.Sc.)
- Brick Seminar in Informatics (Bachelor) | Information Engineering and Management (B.Sc.)
- Brick Seminar in Informatics B (Master) | Information Engineering and Management (M.Sc.)
- Brick Seminar in Informatics B (Master) | Economathematics (M.Sc.)
- Brick Seminar in Informatics A (Master) | Economathematics (M.Sc.)
Note
The seminar is intended as a theoretical supplement to lectures such as "Machine Learning". The theoretical basics will be deepened in the seminar. The aim of the seminar is that the participants work individually to analyze a subsystem from the field of robotics and cognitive systems using one or more procedures from the field of AI/ML.
The individual projects require the analysis of the task at hand, selection of suitable procedures, specification and theoretical evaluation of the approach taken. Finally, the chosen solution has to be documented and presented in a short presentation.
Learning objectives:
- Students can apply knowledge from the Machine Learning lecture in a selected field of current research in robotics or cognitive automobiles for theoretical analysis.
- Students can evaluate, document and present their concepts and results.
Recommendations:
Attendance of the lecture machine learning
Workload:
The workload of 3 credit points consists of the time spent on literature research and planning/specifying the proposed solution. In addition, a short report and a presentation of the work carried out will be prepared.