Vorlesung: Embodied Artificial Intelligence - Details

Vorlesung: Embodied Artificial Intelligence - Details

Allgemeine Informationen

Veranstaltungsname Vorlesung: Embodied Artificial Intelligence
Veranstaltungsnummer INF-0509
Semester SS 2026
Aktuelle Anzahl der Teilnehmenden 15
erwartete Teilnehmendenzahl 18
Heimateinrichtung Professur für intelligente Perzeption in technischen Systemen - Prof. Dr. Jörg Stückler
Veranstaltungstyp Vorlesung in der Kategorie Lehre
Erster Termin Dienstag, 14.04.26, 12:15 - 13:45 Uhr F1 202 (Eichleitnerstrasse 30)
Veranstaltung findet in Präsenz statt / hat Präsenz-Bestandteile Ja
Hauptunterrichtssprache englisch
ECTS-Punkte 8

Räume und Zeiten

F1 202 (Eichleitnerstrasse 30)

  • Dienstag, 12:15 - 13:45, Wöchentlich (ab dem 14.04.26)
  • Dienstag, 14:00 - 17:15, Wöchentlich (ab dem 14.04.26)

Modulzuordnungen

Kommentar/Beschreibung

Robotics research is currently making significant progress due to advances in learning methods, foundation models, highly parallizable simulations, and capable robot hardware. This opens up new perspectives for robotics applications in everyday environment such as our homes or in flexible production.

These developments are often summarized as "embodied artificial intelligence" (embodied AI). While classical AI methods often abstract away the physical world (for example, symbolic blocks world) and break in unforeseen situations, embodied AI learns perception and action by interaction with the environment.

This course teaches fundamentals and contemporary methods for embodied artificial intelligence. Topics include modern reinforcement learning, imitation learning, foundation models for robotics, and scene perception. It consists of a lecture part and an exercise part in which students will gain practical experience in team projects on robot learning and perception methods.

The number of participants in this course is limited. Please register preliminarily in the course if you are interested to participate. Places in the course will be assigned by the course organizers after the lecture in the first lecture week. We will introduce the organizational details of the course in the first lecture.

Prerequisites for this course:
- Basic programming knowledge in Python
- Basic knowledge in Deep Learning

Anmeldemodus

Die Auswahl der Teilnehmenden wird nach der Eintragung manuell vorgenommen.

Please register preliminarily if you are interested to participate in this course.

The number of participants in this course is limited. Places in the course will be assigned by the course organizers after the lecture in the first lecture week. We will introduce the organizational details of the course in the first lecture slot. Participation in this preliminary meeting is important.