Robotics
Robotics is an interdisciplinary field of research and at the same time a key technology that contributes significantly to solving societal and economic challenges and to improving our quality of life. The study profile is designed in an interdisciplinary way, so that the main issues of autonomous and cognitive robotics are addressed both from the algorithmic point of view (e.g. perception, action generation, learning) and from the technical point of view (construction and function of robot components and robot systems).
Graduates of the study profile will have competencies to design, program, and evaluate robotic systems. These include: mathematical and algorithmic foundations of robotics, programming by demonstration and imitation learning, active visual and haptic perception, learning procedures in robotics; grasping and mobile packaging, architectures in robotics, simulation in robotics, humanoid robotics, service robotics, medical robotics, wearable robot technologies (exoskeletons, prostheses/orthotics), industrial robotics, Industry 4.0, process automation, and human-robot interfaces for intuitive robot programming.
German name: Robotik
Designated Speaker / Deputy Speaker: Prof. Tamim Asfour/ Prof. Torsten Kröger
Specific competencies acquired in the profile:
- Graduates know the fundamentals and advanced methods of robotics and can apply these methods when designing robot systems.
- They can handle current technologies and tools for the development and programming of robot systems.
- Master thesis in the field of robotics.
- One of the two advanced mandatory modules "Robotics I - Introduction to Robotics"
(until WS 24/25: Robotik I - Einführung in die Robotik) or "Echtzeitsysteme" (selectable until SS 2024) must be taken. If the advanced mandatory modules have already been examined in the Bachelor's degree, more CP from the event list must be taken. - At least 44 CP from the event list must be taken.
- Further thematically appropriate seminars, practical courses or practice of research can be taken in consultation with the profile coordinator.
- One of the minor studies "Mathematik", "Theoretische Physik", "Experimentalphysik", "Elektrotechnik und Informationstechnik" or "Biologically Inspired Robotics" must be taken.
- A total of at least 50 LP from 2.-4 must be completed.
V=Vorlesung (Lecture), S=Seminar (Seminar), P=Praktikum (Practical course), Ü=Übung (Practice)
(at least 6 CP) |
Course | Module | Partial achievement | CP | Course type |
Echtzeitsysteme (advanced mandatory module) selectable until SS 2024 |
M-INFO-100803 | T-INFO-101340 | 6 | V | |
Robotics I - Introduction to Robotics (advanced mandatory module) until WS 24/25: Robotik I - Einführung in die Robotik |
M-INFO-107162 (M-INFO-100893) |
T-INFO-114190 (T-INFO-108014) |
6 | V | |
List of courses (at least 44 CP) | Course | Module | Partial achievement | CP | Course type |
Biologisch Motivierte Robotersysteme |
M-INFO-100814 | T-INFO-101351 | 3 | V | |
Explainable Artificial Intelligence |
M-INFO-106302 |
T-INFO-112774 |
3 |
V |
|
Forschungspraktikum Autonome Lernende Roboter | M-INFO-105378 | T-INFO-110861 | 6 | P | |
Humanoid Robots – Seminar bis WS 24/25 : Seminar: Humanoide Roboter |
M-INFO-107152 (M-INFO-102561) |
T-INFO-114170 (T-INFO-105144) |
3 | S | |
Innovative Konzepte zur Programmierung von Industrierobotern | M-INFO-100791 | T-INFO-101328 | 4 | V | |
Lokalisierung mobiler Agenten | M-INFO-100840 | T-INFO-101377 | 6 | V | |
Machine Learning - Foundations and Algorithms |
M-INFO-107169 (M-INFO-105778) (M-INFO-105252) |
T-INFO-114197 (T-INFO-111558) (T-INFO-110630) |
6 | V/Ü | |
Motion in Human and Machine - Seminar | M-INFO-102555 | T-INFO-105140 | 3 | S | |
Mustererkennung | M-INFO-100825 | T-INFO-101362 | 3 | V | |
Praktikum: Mobile Roboter |
M-INFO-102977 | T-INFO-105951 | 6 | V | |
Praktikum: Biologisch Motivierte Roboter until SS 24 |
M-INFO-105495 | T-INFO-111039 | 6 | P | |
Projektpraktikum: Robotik und Automation I (Software) | M-INFO-102224 | T-INFO-104545 | 6 | P | |
Projektpraktikum: Robotik und Automation II (Hardware) | M-INFO-102230 | T-INFO-104552 | 6 | P | |
Reinforcement Learning | M-INFO-105623 | T-INFO-111255 | 5 | V | |
Research Project Deep Learning for Robotics |
M-INFO-107174 (M-INFO-105480) |
T-INFO-114203 (T-INFO-111024) |
6 | P | |
Riemannsche Methoden zum Lernen in der Robotik (not applicable from WS 24/25) | M-INFO-105791 | T-INFO-111589 | 3 | V | |
Robotics - Practical Course |
M-INFO-107155 (M-INFO-102522) |
T-INFO-114172 (T-INFO-105107) |
6 | P | |
Robotics II - Humanoid Robotics |
M-INFO-102756 (M-INFO-107123) |
T-INFO-114152 (T-INFO-105723) |
3 | V | |
Robotics III - Sensors and Perception in Robotics |
M-INFO-107130 (M-INFO-104897) |
T-INFO-114155 (T-INFO-109931) |
3 | V | |
Robotik in der Medizin (not applicable from WS 22/23) | M-INFO-100820 | T-INFO-101357 | 3 | V | |
Seminar: Intelligente Industrieroboter | M-INFO-102212 | T-INFO-104526 | 3 | V | |
Seminar: Neuronale Netze und künstliche Intelligenz | M-INFO-102412 | T-INFO-104777 | 3 | S | |
Seminar: Robotik und Medizin | M-INFO-102211 | T-INFO-104525 | 3 | S | |
Seminar: Robot Reinforcement Learning | M-INFO-105379 | T-INFO-110862 | 3 | S | |
Wearable Robotic Technologies Until WS 24/25: Anziehbare Robotertechnologien |
M-INFO-107113 |
T-INFO-114145 (T-INFO-106557) |
4 | V | |
maximum 6 CP from: | |||||
Automatische Sichtprüfung und Bildverarbeitung | M-INFO-100826 | T-INFO-101363 | 6 | V | |
Digitale Barrierefreiheit und Assistive Technologien until WS 21/22: Barrierefreiheit - Assistive Technologien für Sehgeschädigte |
M-INFO-105882 |
T-INFO-111830 (T-INFO-101301) |
3 | V | |
Einführung in die Bildfolgenauswertung | M-INFO-100736 | T-INFO-101273 | 3 | V | |
Informationsverarbeitung in Sensornetzwerken (until SS 2024) |
M-INFO-100895 | T-INFO-101466 | 6 | V |