Nach positiver Absolvierung der Lehrveranstaltung sind Studierende in der Lage...

• Understand the challenges of robotics in manufacturing
• Getting familiar with the concepts of human-robot collaboration and future trends
• Getting to know concepts of Product development
• Integration and manipulation of robotics applications in the simulation environment

Following topics will be presented and discussed in the course:

• Robotics in manufacturing
• Mobile robotics
• Assistant robots
• Safety in Robotics
• Machine learning (Reinforcement learning, transfer learning)
• Innovation and entrepreneurship

The course is structured in three phases that are graded separately:

1. 1. Lectures and exam: The course consists of nine individual lectures covering the content of robotics challenges. An exam will be conducted at the end of the semester. (25% of the grade)
   2. Individual assignments: Two individual assignments will be handed out, covering topics such as systematic literature review in related topics, simulation of work systems, and analysis of them. (20% of the grade)
   3. Project: In the project, students should use what they have prepared in the assignment as a baseline and create a user study experience to analyze the system from different perspectives. More information will be provided within tutorials. (45% of the grade)

   The results should also be documented in the format of a scientific report and presented during the demo day. (10% of the grade)

Der Kurs wird wie folgt benotet:

Prüfung und Vorlesungen - 25% der Note
Individuelle Aufgabenstellungen - 20% der Note
Projekt - 45% der Note
Dokumentation und Präsentation - 10% der Note

Students are expected to understand basic concepts of programming (e.g. Python or another OOP language). Previous knowledge on simulation in Robot Operating System (ROS) and Gazebo is beneficial, but not a prerequisite.