Assistenzrobotik

Summer

(engl. Assistance robotics )

Angestrebte Lernergebnisse:
Graduates of this module ...

• know mathematical transformations for the geometric and differential description of robot kinematics
• know the equation of motion of robot manipulators and can apply it to questions of collaborative safety
• know the different types of interpolation for describing a robot path and can independently generate C² trajectories
• can model the kinematics of mobile robots and determine their position taking into account uncertainties in space
• are familiar with various machine learning methods (unsupervised and supervised learning as well as deep learning) and can classify their possible applications for image processing in the context of robotics
• understand the basic principles of reinforcement learning and know how it can be used to generate optimal handling strategies for robots
• know the basics of machine safety (risk assessment and CE marking)
• know the safety operating modes for collaborative robot systems and can apply them

Inhalt:

• Introduction to assistance robotics
• Fundamentals of assistance robotics (modeling of robot kinematics, path planning, motion and force control, sensors, mobile systems)
• Human-robot collaboration and safety: technologies, machine safety, standards, legal situation
• AI processes in robotics

Arbeitsaufwand:
42h attendance time + 138h independent work

Hinweise: