Master Thesis - Multi-session global traversability Mapping for Autonomous Outdoor Navigation
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Advertisement for the field of study such as: Automation technology, electrical engineering, computer science, cybernetics, mechanical engineering, mechatronics, 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. For mobile robots operating in outdoor, unstructured environments with unknown terrain conditions, maintaining a consistent, global traversability map is essential. Such a map allows the robot to plan long-range, environment-aware routes and avoid obstacles effectively over extended distances. For this purpose, it is essential to develop a robust mapping algorithm, that allows for continuous, online map growth during exploration and mapping operations. The map architecture must be optimized for memory efficiency, and it must incorporate effectively localization information and uncertainty, allowing for loop-closure corrections to reposition and align all maps generated throughout the robot’s trajectory. Additionally, in large and dynamic agricultural environments, it is often impractical to completely map the environment in a single session. Therefore, the mapping architecture needs to allow for multi-session mapping, where the robot incrementally builds and corrects its map over several missions. It must ensure accurate integration of newly explored areas and continuously update traversed regions, to correct previous mapping errors and adapt to environmental changes.
Be part of change
In this thesis, you will design the algorithm to perform long-term, multi-session traversability mapping of static environments. You will evaluate different mapping configurations, focusing on submap-based approaches, which divide the environment into smaller, independent submaps. In particular, you will evaluate how to relate, update and merge these maps along the robot’s trajectory to support multi-session mapping. You will also ensure that the mapping architecture can support loop closure corrections detected by an external localization module. You will then implement your solution inside our ROS2, C++ navigation stack and integrate it with existing components such as the LiDAR-Inertial localization module. Its performance will then be tested both in simulation and in real-world scenarios with our mobile CURT robots.
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We value and promote the diversity of our employees' skills and therefore welcome all applications – regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Our tasks are diverse and adaptable – for applicants with disabilities, we work together to find solutions that best promote their abilities. The same applies if they do not meet all the profile requirements due to a disability.
With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.
Ready for a change? Then apply now with your resume, cover letter and a Transcript of Records and make a difference! Once we have received your online application, you will receive an automatic confirmation of receipt. We will then get back to you as soon as possible and let you know what happens next.
Ms. Jennifer Leppich Recruiting +49 711 970-1415 jennifer.leppich@ipa.fraunhofer.de
Fraunhofer Institute for Manufacturing Engineering and Automation IPA
Requisition Number: 82291 Application Deadline:
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