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#40305 / #7

Seit WS 2019/20


Applications of Robotics and Autonomous Systems


Albayrak, Sahin




Fakultät IV

Institut für Wirtschaftsinformatik und Quantitative Methoden

34361200 FG Agententechnologien in betrieblichen Anwendungen und der Telekommunikation (AOT)

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TEL 14

Xu, Yuan


Learning Outcomes

The students will have an in-depth knowledge and hands-on experience on emerging fields of Robotics and Autonomous Systems (RAS) towards a smooth transition from theoretical knowledge to their applications in dynamic real-time environments. They will experience a full R&D project cycle covering researching, positioning, designing, developing and evaluating (testing on real systems or on simulation). They will gain deeper insights into the scientific and technological aspects of existing solutions in artificial intelligence and multi-agent systems. The students will experience various perception, cognition, learning and planning problems in RAS, will have improved programming skills in real applications, and will get familiar with Robotic Operating System (ROS).


The projects comprise of a selection of topics / problems in line with the department’s research and development activities. These topics will be from emerging fields of RAS, for example: - Autonomous Driving (SLAM, motion, navigation and traffic planning), - Autonomous Smart Factory (optimization in production, autonomous warehousing), - Human-Robot Collaboration (robot perception, human-aware planning). An introduction to ROS, selected simulation environments (e.g. MORSE) and the available real systems (HWs) will be provided by lectures as well as a number of suggested topics. The students will be formed into teams each focusing on one of the selected topics. Throughout the semester, the teams will further detail their topics into design descriptions, system architectures and finally applied systems with validated results. The topics will be implemented regarding the multi-agent nature of autonomous systems. Relevant testbeds as well as a close supervision will be provided to the students. The topics overall cover the technical work below: - autonomous driving: localisation, motion and navigation planning, - multi-robot planning: autonomous warehousing with traffic management, - human-aware planning: human activity recognition (HAR), stochastic planning with collaborative robots including autonomous cars, - machine learning for real-world applications applied to the topics above (e.g. reinforcement learning, deep learning).

Module Components


All Courses are mandatory.

Course NameTypeNumberCycleLanguageSWSVZ
Applications of Robotics and Autonomous SystemsPJ0435 L 759bWiSe/SoSeNo information4

Workload and Credit Points

Applications of Robotics and Autonomous Systems (PJ):

Workload descriptionMultiplierHoursTotal
270.0h(~9 LP)
The Workload of the module sums up to 270.0 Hours. Therefore the module contains 9 Credits.

Description of Teaching and Learning Methods

Weekly project meetings, lectures towards the selected topics or used frameworks (ROS), supervised project works in small groups, system design description, milestones, final report and demonstration/presentation.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

There are no specific prerequisites for this module. A general knowledge of programming (e.g. python, C/C++) and an overall interest in robotics are sufficient.

Mandatory requirements for the module test application:

This module has no requirements.

Module completion



Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte insgesamt



Test elements

Ergebnisprüfung: Design25written2 weeks
Ergebnisprüfung: Evaluation and documentation25written2 weeks
Ergebnisprüfung: Final presentation and review20oral90 minutes
Ergebnisprüfung: Implementation and Test30practical5 weeks

Grading scale

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«


Test description (Module completion)

Die Gesamtnote gemäß § 47 (2) AllgStuPO wird nach dem Notenschlüssel 2 der Fakultät IV ermittel.

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:
Winter- und Sommersemester.

Maximum Number of Participants

The maximum capacity of students is 15.

Registration Procedures

Qispos oder Prüfungsamt und zusätzlich durch Registrierung auf der ISIS-Kursseite. The module can take upto 15 students, but it may change according to the available topics each semester

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable


Electronical lecture notes

Availability:  available
Additional information:
Lehrmaterial wird auf der ISIS-Seite bereitgestellt.



Recommended literature
No recommended literature given

Assigned Degree Programs

This module is used in the following Degree Programs (new System):

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Computer Engineering (M. Sc.)130WS 2019/20SoSe 2024
Computer Science (Informatik) (M. Sc.)140WS 2019/20SoSe 2024
Elektrotechnik (M. Sc.)120WS 2019/20SoSe 2024
ICT Innovation (M. Sc.)230WS 2019/20SoSe 2024
Information Systems Management (Wirtschaftsinformatik) (M. Sc.)214WS 2019/20SoSe 2024
Wirtschaftsingenieurwesen (M. Sc.)122WS 2019/20SoSe 2024


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