After successful completion of the course, students are able to utilize advanced algorithms, concepts, and techniques from the domain of autonomous mobile robotics, and to apply as much as to improve them within research and development.
This course covers advanced algorithms and methodologies from the domain of autonomous as much as semi-autonomous robotic systems like self-driving cars, drones, or search-and-rescue robots. Therefor, selected topics from the area of cognitive vision, probabilistic robotics, deep reinforcement learning and decision making are discussed, and will also be implemented and applied to specialized robotic hardware by students.
In this course, dissemination is achieved by presentation, as much as by hands-on tutorials and practical implementation work for specific tasks on real robotoc hardware within small teams of participants.
Due to the unpredictable status of COVID-19 and releated restrictions and directives of the vice rectorate for academic affairs, the dean's office of academic affairs and of the Ausrian federal government, the lecture is conducted in hybrid mode. The advantages of the directness of face-to-face course meetings shall be preserved to the largest possible extent. All course meetings will thus be held either face-to-face or as real-time video conferences. The modus operandi of each individual lecture will be announced in advance in TISS.
Online via Zoom: https://tuwien.zoom.us/j/6359566675
Online lectures will be conducted via Zoom.
Participation in lecture 185.A51 (Programming Principles of Mobile Robotics) prior to this lecture is highly recommended.
