7 papers
Exploring LLM Capabilities for Situational Understanding and COLREG compliance on real-world maritime navigation scenarios
Julius Wirbel, P. Nicholas Hansen, Line K. H. Clemmensen +1
Recently, Large Language Models (LLMs) have shown considerable capability for situational understanding, reasoning, and decision making in different domains, most notable in the au…
Reinforcement Learning for Heterogeneous Sensor Selection in Maritime Surveillance
Andrei Starodubov, Yaqub Aris Prabowo, Andreas Hadjipieris +2
This paper presents an information-gain-guided reinforcement-learning sensor-selection framework for single-vessel tracking in heterogeneous maritime sensor networks. The proposed…
Closed Form Modelling and Identification of Banking Effects in Confined Waters
Jeppe H. Mikkelsen, Thomas T. Enevoldsen, Bugge T. Jensen +3
Vessels navigating in confined waters are subject to banking effects, which are hydrodynamic forces and moments arising from pressure differentials between the vessel sides, signif…
Distributed Planning for Rigid Robot Formations with Probabilistic Collision Avoidance
Jeppe Heini Mikkelsen, Vit Kratky, Roberto Galeazzi +2
This paper presents a distributed method for robots moving in rigid formations while ensuring probabilistic collision avoidance between the robots. The formation is parametrised th…
Optimal Distributed Multi-Robot Communication-Aware Trajectory Planning using Alternating Direction Method of Multipliers
Jeppe Heini Mikkelsen, Roberto Galeazzi, Matteo Fumagalli
This paper presents a distributed, optimal, communication-aware trajectory planning algorithm for multi-robot systems. Building on prior work, it addresses the multi-robot communic…
Codification of Good Seamanship in Complex and Congested Waterways
Yaqub Aris Prabowo, Peter Nicholas Hansen, Dimitrios Papageorgiou +1
This paper presents a novel method to quantify seafarers' good seamanship during navigation scenarios with multi-vessel encounters -- in open and confined waters --, and to compute…
Optimal Multi-Robot Communication-Aware Trajectory Planning by Constraining the Fiedler Value
Jeppe Heini Mikkelsen, Roberto Galeazzi, Matteo Fumagalli
The paper present a novel approach for the solution of the Multi-Robot Communication-Aware Trajectory Planning, which builds on a general optimisation framework where the changes i…