151-0323-00L  Hands-on Self-Driving Cars with Duckietown

Lehrveranstaltungen

Katalogdaten

Kurzbeschreibung	This course is a hands-on introduction to self-driving cars using the Duckietown platform. Each student is given a mobile wheeled robot and throughout the class must configure and program.
Lernziel	This course covers the basics of modeling, perception, planning, control, and learning for autonomous systems. The focus is on learning the foundational elements of a robotics platform and understanding how these components integrate and interact. The objective of the class is to provide students with a practical understanding of what it takes to design and operate an autonomous mobile system, from a single unit up to a full fleet of robotic systems.
Inhalt	Perception, planning, modeling, and control, leveraging primarily on vision data.
Skript	Lecture notes, primarily in the form of slides and tutorials, will be accessible from Moodle. Additional materials can also be accessed from the EdX MOOC called "Self-driving cars with Duckietown".
Literatur	Course notes will be provided in an electronic form. These are some books that can be used to provide background information or consulted as references: (1) Siegwart, Nourbakhsh, Scaramuzza - Introduction to autonomous mobile robots; (2) Norvig, Russell - Artificial Intelligence, a modern approach. (3) Peter Corke - Robotics Vision and Control (4) Oussama Khatib, Bruno Siciliano - Handbook of Robotics
Voraussetzungen / Besonderes	Students should have taken a basic course in probability theory, computer vision, and control systems. It is crucial that they are not only familiar but also comfortable with programming (Python), Linux, GIT utilization, and the Robot Operating System (ROS), as these tools will be fundamental throughout the course. A shared space will be available to work with the robots.
Kompetenzen	Fachspezifische Kompetenzen Konzepte und Theorien geprüft Verfahren und Technologien geprüft Methodenspezifische Kompetenzen Analytische Kompetenzen geprüft Entscheidungsfindung geprüft Problemlösung geprüft Soziale Kompetenzen Kommunikation gefördert Kooperation und Teamarbeit gefördert Kundenorientierung gefördert Persönliche Kompetenzen Anpassung und Flexibilität gefördert Kreatives Denken geprüft Kritisches Denken geprüft

Leistungskontrolle

Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird)
Leistungskontrolle als Semesterkurs
ECTS Kreditpunkte	4 KP
Prüfende	A. Censi, M. Di Cicco
Form	benotete Semesterleistung
Prüfungssprache	Englisch
Repetition	Repetition nur nach erneuter Belegung der Lerneinheit möglich.
Zusatzinformation zum Prüfungsmodus	The grade will be determined by the outcome of hardware and software exercises performed throughout the semester.

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Studiengang	Bereich	Typ
Maschineningenieurwissenschaften Master	Kernfächer	W
Robotics, Systems and Control Master	Kernfächer	W
Space Systems Master	Vertiefungsfächer Robotics	W+