Thesis project: Pallet perception through deep learning and sensor fusion

Toyota Material Handling Manufacturing Sweden; Mjölby kommun; On-site; SEK 78,000 - 112,000; Part time

Job summary

Toyota Material Handling Manufacturing Sweden invites applications for a Master thesis focused on developing methods using deep learning to improve pallet perception. The project emphasizes fusing model outputs with RGB/ToF data to localize pallets, in collaboration with Toyota's ML teams, starting January 2027.

The thesis spans 30 hp with 1–2 students, incorporating synthetic and real-world data, and leveraging an NVIDIA GPU in an embedded environment for data processing at Toyota's Mjölby site.

Qualifications

• 3D computer vision expertise required.
• Deep learning / ML specialization required.

Responsibilities

• Train and evaluate deep learning models using different methodologies.
• Develop algorithms for data fusion between sensors and model outputs.
• Evaluate trained models with real-world data and synthetic data, and compare results.

Skills

3D computer vision

Deep learning specialization

Job description

Develop methods using deep learning models to improve the current pallet perception system, with a focus on fusing model outputs with data from other sensors. The main focus will be on general pallet identification and localization.

In your Master Thesis at Toyota, you will work on:

• 2D RGB camera
• Time-of-Flight (ToF) 3D camera
• Correlation between pixels from the RGB camera and points in the 3D point cloud from the ToF camera
• NVIDIA chip in an embedded environment (GPU) for data processing

Tasks include:

• Training and evaluation of deep learning (DL) models using different methodologies
• Algorithm development for data fusion
• Evaluation using real-world data and comparison with training results from a synthetic environment

At Toyota, we work with innovative technologies to develop our autonomous trucks. The thesis project will investigate training methodologies, model architecture, and the selection of suitable model outputs that can be effectively combined with point cloud data to accurately localize a pallet in relation to the camera position. The training data will be generated in synthetic environments, which will be provided as part of the project. Therefore, the gap between synthetic and real-world data will also need to be considered when evaluating the results. The thesis project will be carried out in close collaboration with one of Toyota's teams specializing in machine learning development.

SCOPE

Master thesis 30 hp, 1-2 students

Requirements

• 3D Computer vision
• Deep learning specialization / Machine Learning specialization

Who is Toyota Material Handling?

Toyota Material Handling is a global leader in material handling, and we are making significant investments to meet the needs of the future. At our site in Mjölby, 3,000 employees work across the entire material handling value chain, from development concepts to finished vehicles. Our product range spans from manual hand trucks to autonomous vehicles and innovative energy solutions.

A Sustainable Employer

At Toyota Material Handling, we strive to create a friendly, safe and forward-thinking workplace. Our culture is built on Toyota's core values, where respect and consideration guide us in our daily work. Our ambition is to strengthen our competitiveness by increasing diversity across the organization and embracing our differences. Through our leading environmental initiatives, ambitious climate targets and people-focused policies, we are committed to being a sustainable employer.

Start

January 2027

Latest date for application 2026-11-01.

Instagram: ToyotaMHsweden

Linkedin: Toyota Material Handling Manufacturering Sweden AB

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