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Applications of Robotics and Autonomous Systems

9 LP

English

#40305 / #5

WS 2017/18 - SS 2019

Fakultät IV

TEL 14

Institut für Wirtschaftsinformatik und Quantitative Methoden

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

Albayrak, Sahin

Görür, Orhan Can

lehre@lists.dai-labor.de

POS-Nummer PORD-Nummer Modultitel
2347308 39075 Applications of Robotics and Autonomous Systems

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, setting-up, developing and finalizing (testing on real systems or on simulation). These will have a deeper insight into the scientific and technological aspects of existing solutions in artificial intelligence and multi-agent systems. The students will experience various computer vision, learning and planning problems in RAS, will have improved programming skills (e.g. python / C++) in real applications and get familiar with Robotic Operating System (ROS).

Content

The projects comprise of a selection of topics / problems in line with the department’s research and development activities. These changing topics will be from emerging fields of RAS, for example: - Autonomous Robots in Real-World Tasks (e.g. UAVs, service / companion robots), - Human-Robot Interaction (HRI), - Smart Factory (Industry 4.0), - Autonomous Vehicles, - … An introduction to ROS, selected simulation environments (e.g. Gazebo, MORSE) and the available real systems (HWs) will be given in the first few lectures as well as a number of suggested topics. The topics overall cover, but are not limited to, the technical work below: - complex system architectures / frameworks for autonomous agents, - multi/single-agent planning (in stochastic/deterministic conditions), - perception and cognition of sensory inputs (e.g. 3D camera), e.g. object recognition, human & behaviour recognition - machine learning for real-world applications (e.g. reinforcement learning, deep learning) - human-aware planning (e.g. assistant robots, autonomous cars) - basic robotic tasks: motion planning for manipulation - deployment of a complex real world system

Module Components

Pflichtteil:

All Courses are mandatory.

Course Name Type Number Cycle Language SWS
Applications of Robotics and Autonomous Systems PJ 0435 L 759b WS/SS No information 4

Workload and Credit Points

Applications of Robotics and Autonomous Systems (PJ):

Workload description Multiplier Hours Total
Präsenzzeit 15.0 4.0h 60.0h
Vor-/Nachbereitung 15.0 14.0h 210.0h
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:

No information

Module completion

Grading:

graded

Type of exam:

Portfolio examination

Language:

English

Typ of portfolio examination

100 points in total

Test elements

Name Points Categorie Duration/Extent
Ergebnisprüfung: Abschlusspräsentation und Review 20 oral 90 Minuten
Ergebnisprüfung: Design 25 written ca 2 Wochen
Ergebnisprüfung: Evaluation und Dokumentation 25 written ca 2 Wochen
Ergebnisprüfung: Implementierung und Test 30 practical ca 3 Wochen

Grading scale

1.01.31.72.02.32.73.03.33.74.0
95.090.085.080.075.070.065.060.055.050.0

Test description (Module completion)

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

Duration of the Module

This module can be completed in one semester.

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.

Literature

Recommended literature
No recommended literature given.

Assigned Degree Programs

Zur Zeit wird die Datenstruktur umgestellt. Aus technischen Gründen wird die Verwendung des Moduls während des Umstellungsprozesses in zwei Listen angezeigt.

This module is used in the following modulelists:

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

    Miscellaneous

    No information