DRL enables robots to learn optimal control strategies through autonomous interaction with their environment.

[Thesis, Internship] Deep Reinforcement Learning for Robot Control

05.01.2026, Diplomarbeiten, Bachelor- und Masterarbeiten

Deep Reinforcement Learning (DRL) enables robots to learn optimal control strategies through interaction with their environment. Current research focuses on sample-efficient learning in the real world, finetuning foundation models, and sim-to-real transfer. We offer several thesis topics in these areas. Please find all information and the thesis announcement here: https://nextcloud.in.tum.de/index.php/s/2N6xY7L7pqC5rP3

Please find all information and the thesis announcement here: https://nextcloud.in.tum.de/index.php/s/2N6xY7L7pqC5rP3

Kontakt: oliver.hausdoerfer@tum.de

More Information

https://nextcloud.in.tum.de/index.php/s/2N6xY7L7pqC5rP3