3 papers
stat.AP2024
An open-source framework for data-driven trajectory extraction from AIS data -- the -method
Niklas Paulig, Ostap Okhrin
Ship trajectories from Automatic Identification System (AIS) messages are important in maritime safety, domain awareness, and algorithmic testing. Although the specifications for t…
eess.SY2023
2-Level Reinforcement Learning for Ships on Inland Waterways: Path Planning and Following
Martin Waltz, Niklas Paulig, Ostap Okhrin
This paper proposes a realistic modularized framework for controlling autonomous surface vehicles (ASVs) on inland waterways (IWs) based on deep reinforcement learning (DRL). The f…
cs.LG2023
Robust Path Following on Rivers Using Bootstrapped Reinforcement Learning
Niklas Paulig, Ostap Okhrin
This paper develops a Deep Reinforcement Learning (DRL)-agent for navigation and control of autonomous surface vessels (ASV) on inland waterways. Spatial restrictions due to waterw…