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Departments >> Faculty of Engineering >> Department of Electrical-Electronic-Communication Engineering >> Chair of Autonomous Systems and Mechatronics >>

Learning Interfaces for Autonomous Systems (LIAS)2.5 ECTS
(englische Bezeichnung: Learning Interfaces for Autonomous Systems)

Modulverantwortliche/r: Philipp Beckerle, Anany Dwivedi
Lehrende: Anany Dwivedi

Start semester: SS 2022Duration: 1 semesterCycle: jährlich (SS)
Präsenzzeit: 30 Std.Eigenstudium: 45 Std.Language: Englisch

Lectures:

Inhalt:

Human-Machine Interfaces

  • Buttons

  • Hand-held devices

  • Vision/Voice based devices

  • Muscle-Machine Interfaces

Machine learning techniques

  • Signal acquisition and conditioning

  • Different learning methods (regression/classification)

  • Types of classifiers and regressors

Sensor Fusion
Applications of Muscle-Machine Interfaces

  • Teleoperation

  • Shared control framework

  • AR/VR applications

  • Human-Robot Collaboration

The exercise will have group assignments on setting up data acquisition with a simple electromyography (EMG) sensor and applying machine-learning techniques to create a simple interface.

Lernziele und Kompetenzen:

On successful completion of this module, students will be able to:

  • Tackle the interdisciplinary challenges of Human-Machine Interfaces.

  • Understand concepts of machine learning (classification and regression).

  • Implement machine-learning techniques on various datasets.

  • Utilize the learned knowledge to design and implement human-machine interfaces.

Verwendbarkeit des Moduls / Einpassung in den Musterstudienplan:
Das Modul ist im Kontext der folgenden Studienfächer/Vertiefungsrichtungen verwendbar:

  1. Elektrotechnik, Elektronik und Informationstechnik (Master of Science)
    (Po-Vers. 2015s | TechFak | Elektrotechnik, Elektronik und Informationstechnik (Master of Science) | Gesamtkonto | Wahlmodulbereich aus der FAU)

Studien-/Prüfungsleistungen:

Learning Interfaces for Autonomous Systems (Prüfungsnummer: 814540)

(englischer Titel: Learning Interfaces for Autonomous Systems)

Prüfungsleistung, Klausur, Dauer (in Minuten): 60, benotet, 2.5 ECTS
Anteil an der Berechnung der Modulnote: 100.0 %
Prüfungssprache: Englisch

Erstablegung: SS 2022, 1. Wdh.: WS 2022/2023
1. Prüfer: Philipp Beckerle

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