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Friedrich-Alexander-Universität Lehrstuhl für Autonome Systeme und Mechatronik ASM
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  1. Friedrich-Alexander-Universität
  2. Technische Fakultät
  3. Department Elektrotechnik-Elektronik-Informationstechnik
Friedrich-Alexander-Universität Lehrstuhl für Autonome Systeme und Mechatronik ASM
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Summer Semester

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Summer Semester

Sensorik-Praktikum

Das Praktikum befasst sich mit der automatisierten Erfassung und Verarbeitung von Sensor- und Messsignalen. Da es sich um Versuche aus den Gebieten Sensorik mechanischer Größen, Messsignalverarbeitung und Programmierung von Messplätzen handelt, werden hauptsächlich Studenten aus den Studienrichtungen EEI und Mechatronik, aber auch MB und CE angesprochen.

Die Versuche umfassen im Einzelnen die Themen

  • Grundlagen zur graphischen Programmierung mit NI LabVIEW, Generierung und Erfassung von Signalen, virtuelles Oszilloskop, virtueller Funktionsgenerator
  • Messung von Winkel und Drehzahl (Einsatz unterschiedlicher Messprinzipien)
  • Charakterisierung von Störungen und Rauschen, Analyse im Zeit- und Frequenzbereich, Filterung von Messsignalen
  • Was ist „Echtzeit”? Synchronisation von Abläufen, Einsatz von FPGAs

Praktikum Grundlagen der Elektrotechnik III

Im Praktikum Grundlagen der Elektrotechnik III sollen die theoretisch erlangten Kenntnisse der Vorlesung durch praktische Versuche vertieft werden. Im Laufe des Semesters werden die Studenten vier Laborversuche durchführen:

  • Versuch 1: Einschaltvorgänge
  • Versuch 2: Operationsverstärker
  • Versuch 3: Brückenschaltung
  • Versuch 4: Nichtlineare Bauteile

Von den Studenten wird verlangt sich intensiv auf die Versuche vorzubereiten um den größten Lernerfolg zu erreichen.

Das Praktikum gilt als bestanden, wenn alle vier Versuche erfolgreich durchgeführt wurden.

Additional information can be found on: UnivIs

Human-centred Mechatronics and Robotics

Lecturers: Philipp Beckerle,  Adna Bliek 5 ECTS
Semester: SS 2021  Duration: 1 Semester Frequency: annual(SS)
Attendance: 60 hours Self-Study: 90 hours Language: English

Courses:

Human-centred Mechatronics and Robotics (2 SWS, Philipp Beckerle).

Exercises in Human-centred Mechatronics and Robotics (Exercise, 2 SWS, Adna Bliek)

Content:

  • Human-oriented design methods
  • Biomechanics
    • Motions, measurement, and analysis
    • Biomechanical models
  • Elastic robotics
    • Elastic actuators
  • Cognitive and physical human-robot interaction
  • Empirical research methods
    • Research process and experiment design
  • System integration and fault treatment

 

The exercise will combine simulation sessions and a flip-the-classroom seminar where student groups present recent research papers and discuss them with all attendees.

 

Learning objectives and competencies:

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

  • Tackle the interdisciplinary challenges of human-centered robot design.
  • Use engineering methods for modeling, design, and control to develop human-centered robots.
  • Apply methods from psychology (perception, experience), biomechanics (motion and human models), and engineering (design methodology) and interpret their results.
  • Develop robotic systems that provide user-oriented interaction characteristics in addition to efficient and reliable operation.

 

 

Additional information can be found on: UnivIs

Mechatronic Components and Systems

Lecturers: Philipp Beckerle, Rodrigo J. Velasco Guillen 5 ECTS
Semester: SS 2020 Duration: 1 Semester Frequency: annual (SS)
Attendance: 60 hours Self-Study: 90 hours Language: English

Courses:

Mechatronic Components and Systems (Lecture, 2 SWS, Philipp Beckerle)

Exercises in Mechatronic Components and Systems (Excersices, 2 SWS, Rodrigo J. Velasco Guillen)

Content:

  • System thinking and integration
    • Interactions of hardware and software
    • Engineering design methods
  • Mechanical components
  • Actuators
  • Sensors for measuring mechanical quantities
  • Control and information processing

 

Learning objectives and competencies:

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

  • Holistically understand mechatronic systems and optimize them using methods of system integration, control, and information processing.
  • Grundlegende mechanische Komponenten unterscheiden, charakterisieren, modellieren und im Rahmen des Systementwurfs auswählen und dimensionieren.
  • Distinguish, characterize, model, and select basic mechanical components to dimension them in terms of system design.
  • Describe electrodynamic, electromagnetic, fluid power, and unconventional actuators phenomenologically and mathematically to dimension them considering the overall system.
  • Describe sensors for measuring mechanical quantities phenomenologically and mathematically and dimension them taking into account the overall system.

Additional information can be found on: UnivIs

Learning Interfaces for Autonomous Systems

Lecturers:  Anany Dwivedi, Philipp Beckerle  2.5 ECTS 
Semester: SS 2022   Duration: 1 Semester  Frequency: annual(SS) 
Attendance: 24 hours  Self-Study: 50 hours  Language: English 

Courses: 

Learning Interfaces for Autonomous Systems (SS 2022, Lecture, 2.5 SWS, Anany Dwivedi). 

Content: 

  • Human-machine interfaces 
  • Signal conditioning and feature extraction 
  • Machine learning 
  • Sensor fusion 
  • Applications of learning interfaces for autonomous systems 
  • Hands-on sessions: data acquisition using electromyography sensor, signal processing and classification, applications in unity. 

   

Learning objectives and competencies: 

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

  • Distinguish basic components of a human-machine interface and select them appropriately in interface design  
  • Tackle the interdisciplinary challenges of human-machine interfaces. 
  • Understand concepts of machine learning (classification and regression). 
  • Utilize the learned knowledge to design and implement human-machine interfaces. 

  

Additional information can be found on: UnivIs 

Seminar Autonomous Systems and Mechatronics

Lecturers: Anany Dwivedi, Mehmet Ege Cansev, Philipp Beckerle 2,5 ECTS
Semester: SS 2021 Duration: 1 Semester Frequency: semi-annual (WS + SS)
Attendace: 10 hours Self-Study: 65 hours. Language: English

Course:

Seminar Autonomous Systems and Mechatronics (Seminar, 2 SWS, compulsory attendance, Anany Dwivedi, Mehmet Ege Cansev, Philipp Beckerle)

Content:

In the seminar, students will analyze, present. and discuss recent research topics in autonomous systems and mechatronics. This will comprise mechatronic component, system, and control design as well as advanced methods aiming at autonomous operation. Besides reflecting contemporary literature, the students are asked to conclude and suggest directions for future research.

 

Learning objectives and competencies:

On successful completion of this module, students will be able to comprehend and convey recent research challenges in the area of autonomous system and mechatronics. Moreover, they are prepared to infer future research lines from recent developments.
Additional information can be found on: UnivIs

Seminar Cognitive Science in Engineering

Lecturers: Stella Hao, Philipp Beckerle  2,5 ECTS
Semester: SS 2021 Duration: 1 Semester Frequency: annual (SS)
Attendace: 10 hours Self-Study: 65 hours. Language: English

Course:

Seminar Cognitive Science in Engineering  (Seminar, 2 SWS, compulsory attendance, Stella Hao, Philipp Beckerle )

Content:

In the seminar, students will analyze, present. and discuss recent research topics in Cognitve Science and Engineering. Besides reflecting contemporary literature, the students are asked to conclude and suggest directions for future research.

 

Learning objectives and competencies:

On successful completion of this module, students will be able to comprehend and convey recent research challenges in the area of Cognitive Science in Engineering. Moreover, they are prepared to infer future research lines from recent developments.  
Additional information can be found on: UnivIs

 

Lehrstuhl für Autonome Systeme und Mechatronik
Friedrich-Alexander-Universität Erlangen-Nürnberg

Paul-Gordan-Strasse 3/5
91052 Erlangen
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