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151-0606-00L 4 Credits BSC , MSC D-MATH , D-MAVT
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Information processing for robotics

Informationsverarbeitung in der Robotik

Lecturers & Examiners: Dr. Nadine Tschichold-Gürman
VVZ CR n/a

Last Updated: 2026-02-05 15:13:52

Abstract

The lecture gives a short introduction into machine learning techniques, Neural Networks, Fuzzy Logic, Genetic Algorithms and combination of these methods (hybrid models).After a short presentation of the theoretical background, the application of these methods in robotics are presented, the possibilities and the limits of these methods are discussed.

Objective

The objective of the course is to give a short introduction into modern information processing methods and their application in robotics. In particular machine learning techniques, Neural Networks, Fuzzy Logic, Genetic Algorithms and combination of these methods (hybrid models) are addressed.

Content

The topics in the course are: 1. Artificial Intelligence (AI) 1.1. Introduction 1.2. History of AI, lessons learned from the beginnings of AI 2. Neural Networks 2.1. Introduction in Neural Networks 2.1. Perceptrons, Multilayer Perceptrons 2.2. Kohonen's Self Organizing Maps and extensions of H. Ritter 2.3. RuleNet 2.4. Application examples in robotics with these models 3. Fuzzy Logic 3.1 Introduction 3.2 Theory and application examples in robotics 4. Neuro-Fuzzy Systems 5. Genetic Algorithms 5.1 Introduction 5.2 Theory and application examples in robotics 5.3 Genetic Programming 5.4 Combination with Neural Networks 6. Machine Learning Techniques

Resources

Lecture Notes

Copies of the slides will be distributed during the course.

Literature

References to papers and books will be presented during the lectures.

General Information

Language
German
Levels
BSC , MSC
Frequency
Yearly recurring

Examination

Type
session examination
Mode
oral 30 minutes

Course Components

Type Title Time & Place Hours
lecture with exercise Informationsverarbeitung in der Robotik
  • Fri 09:15-12:00 (CLA E 4)
3 h weekly

Offered In