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Isaac Sim, ensuring realistic physics for hybrid locomotion. You will develop and train RL algorithms for hybrid locomotion tasks, including transitioning between locomotion modes and balancing on uneven
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classification algorithms need to be extended with the capability to detect out-of-distribution environments and to autonomously infer their traversability. In this thesis, you will design a semantic
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part of change Driving innovative AI and robotics research Development and implementation, practical application, theoretical analysis and evaluation of AI algorithms Implementation of deep learning and
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guidelines for internship remuneration. The duration of the thesis depends on the requirements of your university. The Fraunhofer-Gesellschaft attaches great importance to the professional equality of women
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the results In addition, you will use algorithms to extract surface characteristics such as roughness, waviness, and contact ratio from the collected data Furthermore, you will develop a machine learning model
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-driving cars or to prevent factory workers from being injured by heavy machines. While AI algorithms may achieve great accuracy in the detection of persons, it is necessary to understand, in which
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the robot and sensors. You will evaluate the methods for completeness, robustness, and runtime on representative datasets and iteratively improve both the setup and the algorithms. What you contribute Very
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optimisation of analytical and numerical models for metasurfaces Documentation of the algorithms developed and results What you contribute You are enrolled in a Master's programme, e.g., computer
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digitization of object geometries, surface characteristics, and material properties. While conventional pipelines rely on generalized camera models, standard calibration targets, and associated algorithms, our
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The Fraunhofer Institute for Algorithms and Scientific Computing SCAI in Sankt Augustin, near Bonn, has around 180 employees who research and develop innovative methods in the field of computational