Model Based Reinforcement Learning for Autonomous Headland Turns

Institut

Lehrstuhl für Agrarmechatronik (WZW)

Typ

Semesterarbeit / Masterarbeit /

Inhalt

experimentell / theoretisch /  

Beschreibung

Minimizing non-working time is a major goal for efficient automated agriculture. Much of this time is
spent turning in the headland. We want to investigate, if Model Based RL can be used to learn the
real vehicle’s model and use this knowledge to quickly optimize the turning behaviour.

Voraussetzungen

• A Bachelor’s level university degree
• Previous Experience with Reinforcement Learning and Mobile Robotics
• An Interest in Agricultural Machinery

Möglicher Beginn

sofort

Kontakt

Lukas Pindl
lukas.pindltum.de

Ausschreibung