Moses - Applications of Robotics and Autonomous Systems

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Diese Modulbeschreibung gilt nicht im aktuellen Semester.

Die Modulbeschreibung gilt nur für den Zeitraum WS 2017/18 - SS 2019. Die Version für das aktuelle Semester (SoSe 2024) finden Sie hier: Modulbeschreibung des SoSe 2024

Module / Version:
#40305 / #5

Validity:
WS 2017/18 - SS 2019

Default display language:
English

Module title:
Applications of Robotics and Autonomous Systems

Credits:
9

Responsible person:
Albayrak, Sahin

Grading:
benotet

Type of exam:
Portfolioprüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Wirtschaftsinformatik und Quantitative Methoden

Area of expertise:
34361200 FG Agententechnologien in betrieblichen Anwendungen und der Telekommunikation (AOT)

Prüfungsausschuss:
No information

Kontakt

Office:
TEL 14

Contact person:
Xu, Yuan

E-mail address:
dai-labor-lehre@lists.tu-berlin.de

Website:

http://www.aot.tu-berlin.de/index.php?id=2887

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	VZ
Applications of Robotics and Autonomous Systems	PJ	0435 L 759b	WiSe/SoSe	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:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte insgesamt

Language

English

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

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Gesamtpunktzahl	1.0	1.3	1.7	2.0	2.3	2.7	3.0	3.3	3.7	4.0
100.0pt	95.0pt	90.0pt	85.0pt	80.0pt	75.0pt	70.0pt	65.0pt	60.0pt	55.0pt	50.0pt

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 literature
No recommended literature given

Assigned Degree Programs

Semester:

Zeige auch ausgelaufene Studiengänge und StuPOs

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

	Studiengang / StuPO	StuPOs	Verwendungen	Erste Verwendung	Letzte Verwendung
This module is not used in any degree program.

Miscellaneous

No information

Applications of Robotics and Autonomous Systems