This seminar course provides a unique overview over central topics in Cyber-Physical-Systems:
- Kinematics, Dynamics & Simulation of CPS
- Data Representations & Model Learning
- Feedback Control, Priorities & Torque Control
- Planning & Cognitive Reasoning
- Reinforcement Learning & Policy Search
The course provides a structured and well motivated overview over modern techniques and tools which enable the students to define learning problems in Cyber-Physical-Systems.
Links and Resources
Location & Time
Learning objectives / qualifications
- Students get a comprehensive understanding of Cyber-Physical-Systems.
- Students learn to analyze the challenges in simulating, modeling and controlling CPS.
- Students understand and can apply advanced model learning and reinforcement techniques to real world problems.
- Students know how to analyze the models’ results, improve the model parameters and can interpret the model predictions and their relevance.
Programming Assignments & Simulation Tools
For simulating CPS we will use the simulator V-REP. For research and for teaching a free eduction version can be found here.
- The Probabilistic Machine Learning book by Univ.-Prof. Dr. Elmar Rueckert.
- Bishop 2006. Pattern Recognition and Machine Learning, Springer.
- Barber 2007. Bayesian Reasoning and Machine Learning, Cambridge University Press.
- Murray, Li and Sastry 1994. A mathematical introduction to robotic manipulation, CRC Press.
- B. Siciliano, L. Sciavicco 2009. Robotics: Modelling,Planning and Control, Springer.
- Kevin M. Lynch and Frank C. Park 2017. MODERN ROBOTICS, MECHANICS, PLANNING, AND CONTROL, Cambridge University Press.