14 citations · 19 across the 4 of their papers we have counts for
6 papers
Improved context-sensitive transformer model for inland vessel trajectory prediction
Kathrin Donandt, Karim Böttger, Dirk Söffker
Physics-related and model-based vessel trajectory prediction is highly accurate but requires specific knowledge of the vessel under consideration which is not always practical. Mac…
Short-term Inland Vessel Trajectory Prediction with Encoder-Decoder Models
Kathrin Donandt, Karim Böttger, Dirk Söffker
Accurate vessel trajectory prediction is necessary for save and efficient navigation. Deep learning-based prediction models, esp. encoder-decoders, are rarely applied to inland nav…
Spatial and social situation-aware transformer-based trajectory prediction of autonomous systems
Kathrin Donandt, Dirk Söffker
Autonomous transportation systems such as road vehicles or vessels require the consideration of the static and dynamic environment to dislocate without collision. Anticipating the…
Incorporating Navigation Context into Inland Vessel Trajectory Prediction: A Gaussian Mixture Model and Transformer Approach
Kathrin Donandt, Dirk Söffker
Using data sources beyond the Automatic Identification System to represent the context a vessel is navigating in and consequently improve situation awareness is still rare in machi…
Polynomial Chaos Expanded Gaussian Process
Dominik Polke, Tim Kösters, Elmar Ahle +1
In complex and unknown processes, global models are initially generated over the entire experimental space but often fail to provide accurate predictions in local areas. A common a…
A hybrid prognosis approach for robust lifetime control of commercial wind turbines
Edwin Kipchirchir, Jonathan Liebeton, Dirk Söffker
Dynamic fluctuations in the wind field to which a wind turbine (WT) is exposed to are responsible for fatigue loads on its components. To reduce structural loads in WTs, advanced c…