Master Thesis – Reinforcement Learning for Autonomous Pallet Handling

In Toyota Material Handling Europe we are over 13500 colleagues passionate about supporting companies of all sizes with todays and tomorrows material handling challenges. Because we know that our business and our industry are essential and sometimes even critical for you for daily life and society at large.
In a rapidly growing high-tech industry in fast transformation Toyota Material Handling Europe is stable global and influential. We are committed to continuous improvement and innovation and we aim to strengthen our capabilities as a learning organisation.

About the Thesis
Accurate lifting and placement of pallets is a complex task. It requires high precision detailed knowledge of rack dimensions and locations and often involves time-consuming commissioning procedures. Developing autonomous solutions has the potential to significantly increase efficiency in warehouse operations.

This Master Thesis will focus on applying Reinforcement Learning (RL) in simulation to train forklift agents for autonomous pallet handling tasks.

You will be based at our Innovation Centre in Vallastaden Linköping just a five-minute walk from the university. The Centre offers a dedicated student area where you can collaborate with other Masters students exchange ideas with our engineers and play an active role in the daily dynamics of innovation. You will also have the opportunity to visit our factory and laboratories in Mjölby gaining close insight into our core operations.

Thesis Objectives
The thesis will focus on:

• Training a forklift agent in NVIDIA Omniverse using Reinforcement Learning.
• Developing autonomous strategies for lifting and placing pallets in warehouse racks.
• Evaluating the potential of simulation-based learning for future autonomous forklift functions.

Your Contribution
As a thesis student you will:

• Implement and train RL models for forklift pallet handling.
• Test and refine algorithms in a simulated warehouse environment.
• Analyse results and propose improvements for real-world application.

Your Profile
We are looking for:

• One or two Masters students in Computer Science AI/ML Robotics or related fields.
• Strong programming skills in Python and/or C.
• Experience with Machine Learning algorithms.
• Understanding of Reinforcement Learning concepts.
• Familiarity with algorithm design and implementation.
• Experience with simulation environments such as Omniverse or Unity. (a plus but not mandatory).

What We Offer

• A unique opportunity to conduct your thesis within a global leader in material handling solutions.
• Access to experts and resources in a dynamic R&D environment.
• Support and mentorship from professionals at both the company and RISE throughout the whole process.
• Compensation according to Toyota Material Handling Europes policy for thesis students.

Practical Information
Start date: January 2026
Duration: Typically 20 weeks aligned with your programme. (30hp)
Location: Linköping / Mjölby Sweden (Innovation Centre with option for remote work)

Your Application
Send your application as soon as possible and no later than November 6th 2025. We review applications continuously so dont wait to apply. Were not looking for perfect. Were looking for curious courageous creative minds who want to MOVE the World with us.

Applications should include:

• CV
• A short personal letter
• Transcript of records

For more information about this thesis topic please contact Vasileia Kampouraki AI and Machine Learning Engineer at

For questions about the recruitment process please contact Victoria Östryd Söderlind;

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