INTERNSHIP DETAILS

Master Thesis: Long-term Global Mapping for Autonomous Outdoor Navigation

CompanyFraunhofer-Gesellschaft
LocationStuttgart
Work ModeOn Site
PostedAugust 3, 2026
Internship Information
Core Responsibilities
Develop a robust mapping framework for autonomous mobile robots to handle long-term global mapping in dynamic outdoor environments. The role involves addressing challenges related to localization uncertainty, temporal inconsistency, and the distinction between static and dynamic obstacles.
Internship Type
full time
Company Size
295
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Fraunhofer IGD is the international leading institute for applied research in visual computing. Visual computing is image- and model-based information technology and includes computer graphics and computer vision, as well as virtual and augmented reality. In simple terms, the Fraunhofer researchers in Darmstadt, Rostock, and Kiel are turning information into images and extracting information from images. In cooperation with its partners, technical solutions and market-relevant products are created. Prototypes and integrated solutions are developed in accordance with customized requirements. In doing so, Fraunhofer IGD places users at the forefront, providing them with technical solutions to facilitate computer work and make it more efficient. Owing to its numerous innovations, Fraunhofer IGD raises man-machine interaction to a new level. Man is able to work in a more result-oriented and effective way by means of the computer and visual computing developments.
About the Role

Call for applications for the field of study such as: automation technology, electrical engineering, computer science, cybernetics, mechanical engineering, mathematics, mechatronics, physics, control engineering, software design, software engineering, technical computer science or similar. 

 

In the research group navigation of mobile robots, we develop autonomous, mobile robots for a variety of outdoor applications, such as agriculture, forestry and logistics. We focus on developing both an autonomous outdoor navigation solution and the hardware of the robots.

 

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Maintaining and updating a consistent global costmap is essential for mobile robots operating in big, unstructured and highly-dynamic outdoor environments, as they allow the robot to plan long-range, environment-aware routes and avoid obstacles effectively over extended distances. The environments where the robot operates are expected to experience large temporal variations due to weather conditions, seasonal changes, new/modified infrastructure, and dynamic obstacles. Therefore, the mapping approach must adapt accordingly, distinguishing between permanent structural changes and temporary variations, ensuring that only relevant static features are integrated over time.

 

The development of a robust mapping framework presents two main challenges. First, it must handle the uncertainty and temporal inconsistency of the localization estimates. Loop closures or other optimization steps in the localization module can introduce drastic corrections to the absolute poses of previous timestamps, requiring the mapping framework to update the map accordingly. Second, it must handle dynamic obstacles and temporary changes, ensuring they are not added to the global static map representation.

 

The following master thesis aims to resolve the previously stated challenges, developing a robust mapping framework that allows for accurate and consistent online map growth during exploratory tasks while efficiently adapting the map to reflect structural changes during long-running robot operations.

Key Skills
Autonomous NavigationRoboticsMappingComputer ScienceControl EngineeringSoftware EngineeringMechatronicsElectrical EngineeringMathematicsPhysicsAutomation TechnologyLocalizationPath PlanningSensor Fusion
Categories
TechnologyEngineeringScience & ResearchSoftware