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areas, could include deep learning (e.g. Long Short Term Memory - LSTM), statistical baselines (e.g. Autoregressive Integrated Moving Average - ARIMA, Kalman filters) and transformers (e.g., spatio
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), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued. Mathematical skills: Competence in mathematical modeling of dynamic systems and
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sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued
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-Making and Route Optimisation: Develop adaptive algorithms within a bias-aware ensemble Kalman filter framework to propose alternative flight paths dynamically. The system will aim to maximise safety and