Master Thesis - Reinforcement Learning for wheeled, bipedal robots

Master Thesis – Reinforcement Learning for Wheeled, Bipedal Robots

Join to apply for the Master Thesis – Reinforcement Learning for Wheeled, Bipedal Robots role at Fraunhofer IPA .

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 behaviors.

Was Sie bei uns tun

• Design and implement a simulation environment for a wheeled, bipedal robot in NVIDIA Isaac Sim, ensuring realistic physics for hybrid locomotion.
• Develop and train RL algorithms for hybrid locomotion tasks, including transitioning between locomotion modes and balancing on uneven terrain.
• Assess the quality and limitations of the training by comparing the simulated behavior with the real‑world performance of our internally developed bipedal robot.

Was Sie mitbringen

• 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.

Was Sie erwarten können

• 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.

Wir wertschätzen und fördern die Vielfalt der Kompetenzen unserer Mitarbeitenden und begrüßen daher alle Bewerbungen – unabhängig von Alter, Geschlecht, Nationalität, ethnischer und sozialer Herkunft, Religion, Weltanschauung, Behinderung sowie sexueller Orientierung und Identität. Schwerbehinderte Menschen werden bei gleicher Eignung bevorzugt eingestellt.

Mit ihrer Fokussierung auf zukunftsrelevante Schlüsseltechnologien sowie auf die Verwertung der Ergebnisse in Wirtschaft und Industrie spielt die Fraunhofer-Gesellschaft eine zentrale Rolle im Innovationsprozess. Als Wegweiser und Impulsgeber für innovative Entwicklungen und wissenschaftliche Exzellenz wirkt sie mit an der Gestaltung unserer Gesellschaft und unserer Zukunft.

Kontakt

Haben wir Ihr Interesse geweckt? Dann bewerben Sie sich jetzt online mit Ihren aussagekräftigen Bewerbungsunterlagen. Wir freuen uns darauf, Sie kennenzulernen!

Frau Jennifer Leppich
Recruiting


Fraunhofer‑Institut für Produktionstechnik und Automatisierung IPA
82451
Bewerbungsfrist:

Seniority level

• Internship

Employment type

• Full‑time

Job function

• Education and Training
• Research Services