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Stuttgart

    Master Thesis - Stuttgart, Deutschland - Fraunhofer-Gesellschaft

    Fraunhofer-Gesellschaft background
    Beschreibung

    What You Will Do

    In this role, you will enhance the robot's environment comprehension by developing a point cloud segmentation technique using classical and/or deep learning methods. Your work will set the groundwork for localization algorithms such as 3D LiDAR SLAM and advanced obstacle identification and avoidance algorithms. You will be tasked with creating and implementing a point cloud segmentation approach to distinguish between dynamic and static objects for better environmental interpretation. Building upon current research, you will assess existing methods and devise a new segmentation concept suitable for diverse outdoor settings. As you implement this using ROS in C++/Python, you will continuously test your algorithms on our outdoor robot platform and assess their performance.

    What You Bring

    • Background in Computer Science, Software Engineering, Electrical Engineering, Mechatronics, or related fields
    • Strong proficiency in C++/Python
    • Hands-on experience with ROS
    • Familiarity with neural networks for image or point cloud processing
    • Analytical mindset and expertise in algorithm development
    • Passion for mobile robotics
    • Fluency in English or German

    What You Can Expect

    • Access to cutting-edge technology in the outdoor mobile robotics domain
    • Practical involvement with our robots on our test grounds in Stuttgart
    • Opportunity to take ownership and bring your innovative ideas to life
    • Collaboration with top students in the field
    • Supportive environment including fun activities like Cake Friday

    We also provide a pathway for outstanding graduates to join us directly.


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