Lecture: Embodied Artificial Intelligence - Details

Lecture: Embodied Artificial Intelligence - Details

General information

Course name Lecture: Embodied Artificial Intelligence
Course number INF-0509
Semester SS 2026
Current number of participants 14
expected number of participants 18
Home institute Professur für intelligente Perzeption in technischen Systemen - Prof. Dr. Jörg Stückler
Courses type Lecture in category Teaching
First date Tuesday, 14.04.26, 12:15 - 13:45 o'clock F1 202 (Eichleitnerstrasse 30)
Veranstaltung findet in Präsenz statt / hat Präsenz-Bestandteile Yes
Hauptunterrichtssprache englisch
ECTS points 8

Rooms and times

F1 202 (Eichleitnerstrasse 30)

  • Tuesday, 12:15 - 13:45, Weekly (from 14.04.26)
  • Tuesday, 14:00 - 17:15, Weekly (from 14.04.26)

Module assignments

Comment/Description

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

Registration mode

After enrolment, participants will manually be selected.

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.