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., Kalman, extended Kalman and particle filters Programming languages such as e.g. Python, C++ and LABVIEW Experience with Robot Operating System (ROS) In the assessment, the emphasis is on the applicant's
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and Kalman filtering techniques. Skills to communicate complex information in a clear and concise manner both verbally and in writing. Skills in visualization and graphical representation. Experienced
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can be deduced from experimental observations. Bayesian data-assimilation techniques, such as Kalman filters [5] or particle filters are of particular interest. These methods would allow
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strive to develop data-driven state estimation and tracking methods beyond Kalman and Particle Filters. We will also develop classification and clustering of complex dynamical processes. The associated
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with Git and GitHub. Experience in machine development and automation. Familiarity with a range of sensors, actuators, and control systems. Experience in the application Kalman filtering is highly
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preferred: Flight control algorithms Extended Kalman filter algorithms Optimization, motion planning algorithms UAV simulation, operation and testing Object oriented programming language, C/C++ and Matlab
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, etc) Experience with state estimation (sensor fusion, Kalman filters, etc) Experience with deep learning software (PyTorch, TensorFlow, etc) Experience with deep reinforcement learning algorithms and
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. Experience in the application Kalman filtering is highly desirable. Experience in mechatronic control system integration with a focus on PID controllers. Understanding of real-time operating systems (RTOS) and
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programs for mechatronic systems. Familiar with version control with Git and GitHub. Familiarity with a range of sensors, actuators, and microcontroller systems. Experience in the application Kalman