Winter Term 2022/23
Overview
We offer the following courses in winter term 2022/23:
- Embedded Systems (Bachelor AI, German)
- Software Craftmanship (Master AI/CPS, German)
- Project: Developing a Drink Mixing Machine (Bachelor/Master AI, Master ISE-CE, German/English)
- Project: Bio-signal processing for exoskeletons (Master AI/CPS, German/English)
- Practical: Cyber Physical Systems (CPS Lab) (Master CPS, German)
Lecture with Exercise for Bachelor AIEmbedded Systems (Eingebettete Systeme)
Lecturer: | Prof. Dr. Gregor Schiele (lecture) Christopher Ringhofer (exercise) |
Language: | German |
Turnus: | Winter semester |
Time: | Thu 10:00 - 12:00 (lecture) Tue 12:00 - 14:00 (exercise) |
Place: | LC 137 (lecture & exercise) |
Begin: | 13.10.2022 (lecture) 18.10.2022 (exercise) |
The goal of this course is to understand the characteristics of embedded systems as well as the ability to program embedded systems using the C programming language.
Embedded systems are very small computer systems that have a specific application area. They can be part of more complex systems (cars, household appliances) or autonomous (cell phones, measuring instruments). In the lecture, the characteristics of embedded systems will be discussed. Special emphasis will be put on the problems encountered when developing software for embedded systems on microcontrollers (MCUs), especially for so-called bare-metal systems, i.e. software that runs without operating system support. The following topics will be discussed in the lecture: • The basic architecture of embedded systems (HW/SW) • basic I/O with GPIO ports • working with analog signals • interrupts • timers • digital communication protocols • energy saving approaches • code optimization.
Lecture with exercise for Master AI & CPSSoftware Craftmanship
Lecturer: | Prof. Dr. Gregor Schiele (lecture) Lukas Einhaus (exercise) |
Language: | German |
Turnus: | Winter semester |
Zeit: | Mon 14:00 - 16:00 (lecture) Mon 16:00 - 18:00 (exercise) |
Place: | BC 303 (lecture & exercise) |
Begin: | 17.10.2022 |
Project for BAI, MAI & Master ISE Computer EngineeringDeveloping a Drink Mixing Machine
Lecturer: | Prof. Dr. Gregor Schiele Lukas Einhaus |
Language: | German/English |
Turnus: | Winter semester |
Time: | Tue 14:00 - 15:30 |
Place: | BC 013 |
Begin: | 11.10.2022 |
In this course a PCB and software should be developed for an existing mechanical drink mixing machine. The machine has different actuators. I’ll expect the group to split up, so everyone can do what they’re good in. Ideally the following steps are performed by someone in the group:
- Design PCB for IO(Motordrivers, Sensors)
- Design PCB for an controlling MCU and connect it with IO-PCB
- Programm the controlling MCU
- Develop an Idea for the UI on Raspberry PI (optional)
- Programm the RPI and UI for the existing touch screen (optional)
- Connect the RPI and the controlling MCU (optional)
Organisation:
The kickoff meeting for this project will be on the 11. Oct. 2022 at 14:00-15:30 in Room BC 013. Attendance in the kickoff meeting is mandatory for participation in this project.
This project is limited to Bachelor/Master Angewandte Informatik and Master ISE Computer Engineering.
Project for MAI and M-CPSBio-signal processing for exoskeletons
Lecturer: | Prof. Dr. Gregor Schiele Chao Qian |
Language: | German/English |
Turnus: | Winter semester |
Time: | 11:00 - 12:00 |
Place: | BC 013 |
Begin: | 12.10.2022 Wednesday (Kickoff) |
Medical exoskeletons are an important topic e.g. for medical rehabilitation of stroke patients. One challenge is to identify what kind of movement a user wants to do, e.g. lifting an arm. This can be supported using biosignal analysis such as EEG (i.e., neuron activity in the brain) or EMG (i.e., muscle activity). In this project, we will explore how embedded machine learning can be used to implement better exoskeletons through such biosignal analysis.
- explore the state of the art for biosignal analysis for exoskeleton control,
- design and train machine learning (ML) algorithms for biosignal analysis (EEG, EMG),
- use an existing toolchain to implement embedded accelerators for such ML algorithms,
- evaluate the developed system with real experiments.
- Experience with C/C++ programming
- Prior knowledge of time series analysis and / or digital signal processing
- Experience with designing / training machine learning solutions
- Experience with embedded systems development
- Python or VHDL programming experience
Organisation:
The kickoff meeting for this project will be on the 12. Oct. 2022 at 11:00-12:00 in Room BC 013. Attendance in the kickoff meeting is mandatory for participation in this project.
This project is limited to Master Angewandte Informatik and Master Cyber Physical Systems students.
Lab / PracticalCyber Physical Systems
Lecturer: | Prof. Dr. Gregor Schiele |
Language: | German |
Turnus: | Winter semester |
Time: | 11:00 |
Place: | BC 013 |
Begin: | 10.10.2022 Monday (Kickoff) |
This lab is offered exclusively for students in the new Master-level study program Cyber Physical Systems in cooperation with the groups of Prof. Weis and Prof. Pauli. The kickoff meeting of the CPS lab will be directly after the `CPS Einführungsveranstaltung`. Besides, on 10.10.2022 no Lab session will be held, which means after the meeting you can go home.