This interdisciplinary block seminar addresses methods for modeling, generating, and controlling movements in human and robot systems. Students gain insight into this interdisciplinary field, learning fundamentals of capturing biological motion, biomechanical simulation, robotics, and machine learning.

The seminar begins with the generation of human movement as an effect of muscle contraction. It covers how observed movement patterns can be identified and categorized. Methods for learning movement primitives from human demonstrations are presented, including approaches for reproducing these patterns on humanoid robots. The seminar addresses the challenge of mapping human motion to robots with different kinematics and dynamics. Students learn how motion primitives enable transfer of human movements to robotic systems and their application to motion generation in humanoid robots.

Students work in small groups on collaborative projects that apply the learned methods. These projects allow students to deepen their understanding through practical application of the methods.

Competency Goals:

Students understand methods for modeling, processing, and analyzing human motions. They can explain approaches for capturing biological motion and biomechanical simulation.

Students can describe methods for learning motion primitives from human demonstrations and understand how human motion is mapped to robots with different kinematics and dynamics. They can apply these methods in new contexts.

Students are familiar with the DFG Code of Conduct "Guidelines for Safeguarding Good Scientific Practice" and successfully apply these guidelines in the preparation of their scientific work.

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Institutions:
KIT IAR - H²T Prof. T. Asfour, University of Stuttgart, University of Tübingen 

This interdisciplinary seminar is conducted in cooperation with the University of Stuttgart and the University of Tübingen.

Competency certificate:
The assessment is carried out as an examination of another type (§ 4 Abs. 2 No. 3 SPO) and it includes a term paper and a final presentation.

Recommendations:
Programming skills in C++, Python or Matlab are recommended.
Attendance of the lectures Robotics I – Introduction to Robotics, Robotics II – Humanoid Robotics, Robotics III – Sensors and Perception in Robotics, Mechano-Informatics and Robotics and Wearable Robot Technologies is recommended.

Workload:
90 h 

• approx. 30 h attendance time
• approx. 15 h group project
• approx. 20 h literature review
• approx. 20 h written paper
• approx.   5 h preparation of video podcast