Master Thesis - Reinforcement Learning for wheeled, bipedal robots

Fraunhofer-Gesellschaft; Stuttgart; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A leading research institution in Stuttgart is seeking a motivated student for a thesis project focused on mobile robotics. You will design simulation environments for bipedal robots and develop Reinforcement Learning algorithms. The ideal candidate will have a background in Computer Science or related fields. Join a dynamic team and gain hands-on experience while working with cutting-edge technology. The position offers a friendly atmosphere and opportunities to implement your own ideas.

Leistungen

Cutting-edge technology in outdoor mobile robotics

Hands-on experience with robots

Friendly atmosphere including Cake Thursday

Qualifikationen

• Valid enrollment at a German university.
• Experience with Reinforcement Learning and Physics Engines is a plus.
• Enthusiasm for mobile robotics.

Aufgaben

• Design and implement a simulation environment for a bipedal robot.
• Develop and train RL algorithms for hybrid locomotion tasks.
• Compare simulated behaviour with real-world performance.

Kenntnisse

Reinforcement Learning

Analytical mindset

Fluent in English or German

Ausbildung

Valid enrollment at a German university/Hochschule

Background in Computer Science, Software Engineering, Mechanical Engineering, Mechatronics

Tools

NVIDIA Isaac Sim

Physics Engines

ROS

Jobbeschreibung

Advertisement for the field of study such as

automation technology, electrical engineering, computer science, cybernetics, aerospace engineering, mechanical engineering, mathematics, mechatronics, physics, control engineering, software design, software engineering, technical computer science or comparable.

In the Professional Service Robots - Outdoor research group we develop autonomous, mobile robots for a variety of outdoor applications, such as agriculture, forestry and logistics. The focus is on the development of an autonomous outdoor navigation solution as well as the hardware of the robots.

Wheeled, bipedal robots combine the advantages of dynamic walking with efficient wheeled locomotion. Controlling such systems in real-world environments is challenging due to the high-dimensional dynamics, non-linear contact interactions, and varying surface conditions. Reinforcement learning (RL) offers a promising approach to develop adaptive and robust control policies, but training on physical hardware is often impractical and unsafe. Realistic simulation environments are therefore essential. NVIDIA Isaac Sim with Isaac Lab enables high‑fidelity physics simulation, sensor emulation, and RL‑compatible environments for training and evaluating complex locomotion and navigation behaviours.

What you will do

In this thesis, you will design and implement a simulation environment for a wheeled, bipedal robot in NVIDIA Isaac Sim, ensuring realistic physics for hybrid locomotion. You will develop and train RL algorithms for hybrid locomotion tasks, including transitioning between locomotion modes and balancing on uneven terrain. To assess the quality and limitations of the training, you will compare the simulated behaviour with the real‑world performance of our internally developed bipedal robot.

What you bring to the table

• Valid enrollment at a German university/Hochschule
• Background in Computer Science, Software Engineering, Mechanical Engineering, Mechatronics or similar
• Experience with Reinforcement Learning
• Experience with Physics Engines is a plus
• Experience with NVIDIA Isaac Sim and Isaac Lab is a plus
• Experience with ROS is a plus
• Analytical mindset
• Enthusiasm for mobile robotics
• Fluent in English or German

What you can expect

• Cutting‑edge technology in the field of outdoor mobile robotics
• Hands on with our robots in Stuttgart
• Take on responsibility and freedom to implement your own ideas
• Work with the best students in their discipline
• Familiar atmosphere including Cake Thursday

Interested? Apply online now. We look forward to getting to know you!

Ms. Jennifer Leppich
Recruiting
[phone]
[e-mail]
Fraunhofer Institute for Manufacturing Engineering and Automation IPA
www.ipa.fraunhofer.de
Requisition Number: 82451
Application Deadline: