Course Catalog

Study Program SoSe 2022

Zertifikatsstudium Grundlagen Digitaler Medien in pädagogischen Kontexten

Digitale Medien in Lernumgebungen

Course numberTitle of eventLecturer
01-15-03-IoT(a)-VInternet of Things (in English)

Lecture (Teaching)
ECTS: 6 (4)

Additional dates:
Mon. 19.09.22 09:00 - 18:00 NW1 S1260 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4094
Mon. 19.09.22 09:00 - 18:00 NW1 S1270 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4090
Mon. 19.09.22 09:00 - 18:00 NW1 S1330 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.2070
Mon. 19.09.22 09:00 - 18:00 NW1 S1360 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.1060
Tue. 20.09.22 09:00 - 18:00 NW1 S1270 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4090
Tue. 20.09.22 09:00 - 18:00 NW1 S1260 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4094
Tue. 20.09.22 09:00 - 18:00 NW1 S1330 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.2070
Tue. 20.09.22 09:00 - 18:00 NW1 S1360 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.1060
Wed. 21.09.22 09:00 - 18:00 NW1 S1330 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.2070
Wed. 21.09.22 09:00 - 18:00 NW1 S1360 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.1060
Wed. 21.09.22 09:00 - 18:00 NW1 S1270 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4090
Wed. 21.09.22 09:00 - 18:00 NW1 S1260 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4094
Thu. 22.09.22 09:00 - 18:00 NW1 S1330 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.2070
Thu. 22.09.22 09:00 - 18:00 NW1 S1260 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4094
Thu. 22.09.22 09:00 - 18:00 NW1 S1270 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4090
Thu. 22.09.22 09:00 - 18:00 NW1 S1360 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.1060
Fri. 23.09.22 09:00 - 18:00 NW1 S1260 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4094
Fri. 23.09.22 09:00 - 18:00 NW1 S1270 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4090
Fri. 23.09.22 09:00 - 18:00 NW1 S1330 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.2070
Fri. 23.09.22 09:00 - 18:00 NW1 S1360 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.1060
Mon. 26.09.22 09:00 - 18:00 NW1 S1330 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.2070
Mon. 26.09.22 09:00 - 18:00 NW1 S1360 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.1060
Mon. 26.09.22 09:00 - 18:00 NW1 S1270 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4090
Mon. 26.09.22 - Tue. 27.09.22 (Mon., Tue.) 09:00 - 18:00 NW1 S1260 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4094
Tue. 27.09.22 09:00 - 18:00 NW1 S1270 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4090
Tue. 27.09.22 09:00 - 18:00 NW1 S1330 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.2070
Tue. 27.09.22 09:00 - 18:00 NW1 S1360 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.1060
Wed. 28.09.22 09:00 - 18:00 NW1 S1330 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.2070
Wed. 28.09.22 09:00 - 18:00 NW1 S1360 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.1060
Wed. 28.09.22 09:00 - 18:00 NW1 S1260 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4094
Wed. 28.09.22 09:00 - 18:00 NW1 S1270 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4090
Thu. 29.09.22 09:00 - 18:00 NW1 S1260 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4094
Thu. 29.09.22 09:00 - 18:00 NW1 S1270 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4090
Thu. 29.09.22 09:00 - 18:00 NW1 S1330 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.2070
Thu. 29.09.22 09:00 - 18:00 NW1 S1360 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.1060
Fri. 30.09.22 09:00 - 18:00 NW1 S1260 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4094
Fri. 30.09.22 09:00 - 18:00 NW1 S1270 - Gesperrt ab 01.04.2023 - Ersatz NW2 A4090
Fri. 30.09.22 09:00 - 18:00 NW1 S1330 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.2070
Fri. 30.09.22 09:00 - 18:00 NW1 S1360 - Gesperrt ab 01.04.2023 - Ersatz Unicom 2.1060

Blockkurs, findet in den Räumen S1260, S1270, S1330 und S1360 statt. Zeiten nach Absprache.

Dr. Andreas Könsgen
Prof. Dr. Anna Förster
Dr. Asanga Udugama
03-06-M-313Mathematics. Computer Science. Digital Media. Beginnings (in English)

Seminar (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Tue. 14:00 - 18:00 MZH 1110 Seminar
Frieder Nake
03-IBAP-CS (03-BB-711.01)Cognitive Systems (in English)
Grundlagen der Informationsverarbeitung in natürlichen und künstlichen Systemen

Lecture (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Tue. 08:00 - 10:00 GW2 B1410 Vorlesung Präsenz
weekly (starts in week: 1) Wed. 08:00 - 10:00 CART Rotunde - 0.67 Übung Präsenz
weekly (starts in week: 1) Wed. 10:00 - 12:00 CART Rotunde - 0.67 Übung Präsenz
Thomas Dieter Barkowsky
03-IBAP-ML (03-BB-710.10)Grundlagen des Maschinellen Lernens (in English)
Fundamentals of Machine Learning

Kurs (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Mon. 14:00 - 16:00 MZH 3150 Übung Präsenz
weekly (starts in week: 1) Wed. 10:00 - 12:00 MZH 1380/1400 MZH 6200 Vorlesung Präsenz
weekly (starts in week: 1) Wed. 14:00 - 16:00 MZH 1100 Übung Präsenz

Additional dates:
Wed. 27.07.22 10:00 - 14:00 MZH 1380/1400
Wed. 27.07.22 10:00 - 14:00 MZH 1470

Schwerpunkt: AI

Tanja Schultz
Felix Putze
Mazen Salous
Darius Ivucic
Gabriel Ivucic
03-IBAP-MRCAModern Robot Control Architectures (in English)

Lecture (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Mon. 10:00 - 12:00 Extern RH 1 (DFKI-Gebäude) Raum B0.10 Vorlesung Präsenz
weekly (starts in week: 1) Thu. 14:00 - 16:00 Extern RH 1 (DFKI-Gebäude) Raum B0.10 Übung Präsenz

Robotics is a complex field that emerged at the intersection of multiple disciplines such as physics, mathematics and computer science. New advances in hardware and software design and progress in artificial intelligence enable robotics research to pursue higher goals and achieve increased autonomy in various environments. For instance, robots can operate in disaster zones for search and rescue operations, can be employed in rehabilitation and healthcare, space and underwater exploration, etc. Given the complexity of such scenarios, it is essential to develop robust robotic systems with a high degree of autonomy, able to assist humans in difficult and tedious tasks.

This course aims to provide the fundamentals of modern robot control approaches that enable robotic agents to operate in the environment autonomously. The course introduces a basic understanding of autonomous robots, along with tools and methods to control various types of mobile robotic platforms and manipulators. Firstly, the course presents the types of sensors and actuators employed in autonomous robotic platforms. Secondly, it offers a formal understanding of the robot geometry, its kinematic and dynamic models. Finally, the course provides methods and approaches to control the robotic system from a deliberative and reactive point of view. Students will put this knowledge into practice during tutorials and exercise sheets using Python implementation and robot simulations.

Contents

  • Introduction to Robotics and AI: long term robot autonomy, artificial intelligence, deliberative vs. reactive control, robotic applications.
  • Sensing and Actuation Modalities: types of sensors and actuators, sensor fusion, actuator control.
  • Robot Geometry and Transformations: robot transformations in the 3D space, exponential and logarithmic maps, forward and inverse geometric models.
  • Kinematics: definition of twists and wrenches for rigid bodies, geometric Jacobian formulation, forward and inverse kinematics.
  • Dynamics: an introduction to Lagrangian and Newtonian mechanics, robot dynamics formulation, recursive Newton-Euler algorithm.
  • Localization: direct and probabilistic methods for robot localization, odometry, global localization, particle filter.
  • Path Planning: path vs. trajectory generation, graph-based methods for path planning (e.g. Djikstra, A\*).
  • Kinodynamic Planning: transcribing a dynamic planning problem into trajectory optimization, direct and indirect methods, costs and constraints.
  • Reinforcement Learning-based Control: mathematical foundations, discrete vs continuous methods, reinforcement learning for closed-loop robot control.
  • Dynamic Control: PD gravity compensation control, computed torque control, admittance vs impedance control.
  • Optimal Control: energy-shaping control, LQR and time-varying LQR control.

Learning Outcomes

At the end of the course, the student is expected to be able to:
  • Define robot autonomy and list its key aspects.
  • Describe the sensor and actuator modalities used in robotics, and explain their relevance for robot control.
  • Implement and understand the low-level actuator control methods.
  • Compute the 3D world coordinate transformations for rigid bodies.
  • Apply the robot forward and inverse geometric model.
  • Describe a robotic system based on its kinematic and dynamic properties.
  • Use probabilistic methods for robot localization.
  • Generate an optimal path for a mobile robot or manipulator using graph search methods.
  • Plan a path taking into account the robot kinodynamic properties.
  • Use reinforcement learning methods to control simple robotic systems.
  • Apply dynamical and optimal control methods on robotic systems such that they are robust against disturbances.
  • Assess the strengths and limitations of different control methods presented in the course.
  • Identify open challenges in robotics research and current trends in state-of-the-art.
  • Communicate confidently using the terminology in the field of robotics.
  • Cooperate and work in teams in order to solve tasks.

Examination

a) Submission of 6 worksheets in groups of 4 students and group interview for final grade (Übungsaufgaben und Fachgespräch).
b) Individual oral exam without worksheet submission (mündliche Prüfung).

References

  • Mechanics of Robotic Manipulation, Mathew T. Masen, MIT press, 2001.
  • Algebra and Geometry, Alan F. Beardon, Cambridge University Press, 2005.
  • Modelling and Control of Robot Manipulators, Lorenzo Sciavicco, Bruno Siciliano, Springer, 2000.
  • Probabilistic Robotics (Intelligent Robotics and Autonomous Agents), Sebastian Thrun, Wolfram Burgard, and Dieter Fox, MIT Press, 2005.
  • Introduction to Autonomous Mobile Robots, Siegwart R., Nourbakhsh I., Scaramuzza D., MIT press, 2011.
  • Automated Planning: Theory and Practice, Malik Ghallab, Dana Nau, Paolo Traverso, Elsevier, 2004.
  • Behaviour-based robotics, R. C. Arkin, MIT press, 1998.
  • Modern Robotics: Mechanics, Planning, and Control, Kevin M. Lynch and Frank C. Park, Cambridge University Press, 2017.

Frank Kirchner
M. Sc. Mihaela Popescu (Organizer)
03-IBVA-DS (03-BE-802.98a)Data Science (in English)
Applied Machine Learning

Kurs (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Mon. 16:00 - 18:00 Online Kurs online

From medical decision support systems to automatic language translation, from sorting and prioritizing news on social networks to autonomous cars: Machine learning is woven into the fabric of daily life. Applying machine learning, data science aims to extract knowledge or insights from data.

The class will provide an introduction to data science and applied machine learning. For this, the programming language Python will be used (and taught). You will learn about the difference between supervised and unsupervised machine learning, and four machine learning tasks:
• Classification (e.g. k-NN, Decision Trees, Support Vector Machines)
• Regression (Linear Regression, Logistic Regression)
• Clustering (k-means)
• Dimensionality Reduction (PCA, t-SNE)
We will explore natural language processing for text mining and computer vision. Exploratory data analysis and evaluation, as an integral part of data science, will also be taught.

This class is taught remotely. Every week, the lecturer will upload new material to this website. To succeed in this course, you have to watch the videos, do the exercises and applications, and work on your own project. Remember that these videos are not full-fledged lectures, they are a starting point for your own learning. Use material like the coursebook to learn more about the topics as we progress in the course.

This is an online course, not a lecture that was filmed and put online. The course format was adapted to suit both the needs of the medium and the material.

We will meet regularly, but most of the input will be provided as videos. This allows you to rewatch videos, watch them at different speeds, and discuss the videos with each other.

Prof. Dr. Hendrik Heuer
Dr. Juliane Jarke
03-IMAA-CTHCICurrent Topics in Human Computer Interaction (in English)

Kurs (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Wed. 12:00 - 16:00 MZH 1470 Kurs Präsenz

Profil: DMI
Schwerpunkt: IMA-DMI, IMA-VMC

Prof. Dr. Tanja Döring
Dr. Susanne Putze
Dr. Dmitry Alexandrovsky
03-IMAA-EC (03-MB-804.03)Entertainment Computing (in English)

Lecture (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Tue. 12:00 - 16:00 GW2 B1820 Vorlesung und Übung Präsenz

Profil: DMI
Schwerpunkt: IMK-DMI, IMA-VMC

Prof. Dr. Rainer Malaka
Dr. Dmitry Alexandrovsky
03-IMAP-WCOMP (03-MB-799.01)Wearable Computing (in English)

Lecture (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Wed. 14:00 - 16:00 MZH 1090
weekly (starts in week: 1) Wed. 16:00 - 18:00 MZH 1090

Profil: KIKR, DMI.
Schwerpunkt: DMI, VMC, AI

Dipl.-Inf. Alexej Wagner
03-IMS-AISSeminar on Autonomous and Intelligent Systems (in English)

Seminar (Teaching)
ECTS: 3

Dates:
weekly (starts in week: 1) Tue. 16:00 - 18:00 DFKI RH1 B0.10 Seminar Präsenz

Additional dates:
Tue. 19.07.22 14:00 - 18:00 RH1 B0.10

Profil: KIKR

Frank Kirchner
Melvin Laux
03-IMS-APMSK (03-ME-711.09)Ausgewählte Probleme der multisensorischen Kognition (in English)
Selected Problems of Multisensory Cognition
DIE VERANSTALTUNG ENTFÄLLT

Seminar (Teaching)
ECTS: 3

Dates:
weekly (starts in week: 1) Thu. 12:00 - 14:00 CART Rotunde - 0.67 Seminar Präsenz

Profil: KIKR, DMI.
Die Veranstaltung findet in Englischer Sprache statt.

Christop W. Zetzsche-Schill
Kerstin Schill
03-IMVA-ACSSApplied Computer Science in Sports (in English)

Kurs (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Wed. 14:00 - 16:00 MZH 6200 Vorlesung Präsenz
weekly (starts in week: 1) Wed. 16:00 - 18:00 MZH 6200 Übung Präsenz
weekly (starts in week: 1) Wed. 16:00 - 18:00 MZH 1100 Übung Präsenz

Additional dates:
Wed. 21.09.22 14:00 - 18:00 CART Rotunde - 0.67

Schwerpunkt: AI, DMI
This aim of this course is to create an understanding of the major aspects of sports applications. The course is split into two parts: the first half has a classic lecture/tutorial style, whereas the second half will focus on the creation of individual sports applications.

The lectures will explain the necessary fundamentals, such as sensor technology, user feedback, and the conduction of empirical studies, along with a number of inspiring examples.

In the project part, own prototypes for sports applications are developed in small groups. The exact application as well as the technical implementation approach can be chosen freely. The final graded outcome of the course will be a small sports application about which a presentation has to be held and a documentation in a scientific paper style has to be written.

The course will be held in English.

Schwerpunkt: AI, DMI

Robert Porzel
Dr. Tim Laue
Bastian Dänekas
03-IMVA-EI (03-ME-899.03)Embodied Interaction (in English)

Kurs (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Thu. 10:00 - 14:00 MZH 1450 Kurs Präsenz

Profil: DMI.
Schwerpunkt: DMI, VMC

Robert Porzel
Prof. Dr. Rainer Malaka
03-IMVP-HCIR (03-ME-712.04)Human-Centered Interaction in Robotics (in English)

Lecture (Teaching)
ECTS: 6

Dates:
weekly (starts in week: 1) Mon. 14:00 - 16:00 Extern RH 1 (DFKI-Gebäude) Raum B0.10 Vorlesung Präsenz
weekly (starts in week: 1) Wed. 16:00 - 18:00 Extern RH 1 (DFKI-Gebäude) Raum B0.10 Übung Präsenz

Profil: KIKR
Schwerpunkt: AI

Frank Kirchner
Dr. rer. nat. Teena Hassan
09-60-M8/9-KSocial Movements: Power, Resistance, and Political Dynamics in the Age of Digital Media (in English)

Seminar (Teaching)

Dates:
fortnightly (starts in week: 2) Tue. 12:00 - 14:00 FVG O0150 (Seminarraum) (1 Teaching hours per week)
fortnightly (starts in week: 2) Tue. 14:00 - 16:00 SH D1020 (1 Teaching hours per week)

Description:
https://www.uni-bremen.de/fileadmin/user_upload/fachbereiche/fb9/zemki/docs/comments/Comments_SoSe22/M8_Buettner.pdf

The seminar has 4 hours and takes place every second week, thus both time slots belong together!
Seminar language: English!

Hannah-Marie Büttner
09-60-M8/9-NHuman Rights in the Digital Age (in English)

Seminar (Teaching)

Dates:
weekly (starts in week: 1) Tue. 14:00 - 16:00 GW1 B0100 (2 Teaching hours per week)

Additional dates:
Wed. 20.04.22 13:00 - 15:00 Online
Thu. 28.04.22 13:00 - 15:00 Online
Tue. 07.06.22 16:00 - 18:00 SFG 2020
Tue. 14.06.22 16:00 - 18:00 GW2 B1216
Tue. 28.06.22 14:00 - 18:00 Online


Dennis Redeker
12-55-200Digital Literacy and Language Learning (in English)
Media literacy and language learning

Seminar (Teaching)
ECTS: 3

Dates:
fortnightly (starts in week: 1) Fri. 13:00 - 16:30 GW2 B1632 (2 Teaching hours per week)
N. N.