TY - GEN
T1 - COLREG-Compliant Machine Learning for Safe and Legal Autonomous Maritime Navigation
AU - Treloar, Alfie Anthony
AU - Varghese, Dany
AU - Verma, Shubhi
AU - Tamaddoni-Nezhad, Alireza
AU - Hunter, Alan
PY - 2025/11/25
Y1 - 2025/11/25
N2 - This paper presents preliminary work on integrating symbolic learning and reasoning into autonomous maritime systems using inductive logic programming (ILP). A key challenge in operationalising ILP is bridging the gap between continuous sensing and actuation data and discrete symbolic logic. We propose a framework that enables autonomous vessels to query maritime rules (COLREGs) and learn from human oversight. Using the ILP system PyGol, we demonstrate the learning of COLREG Rule 13 for overtaking situations from discretised bearing data, and further explore the learning of an exception to Rule 15 for crossing situations through examples inspired by case law. These results show the potential for interpretable, legally compliant decision-making and lay the groundwork for learning more complex rules in dynamic maritime environments.
AB - This paper presents preliminary work on integrating symbolic learning and reasoning into autonomous maritime systems using inductive logic programming (ILP). A key challenge in operationalising ILP is bridging the gap between continuous sensing and actuation data and discrete symbolic logic. We propose a framework that enables autonomous vessels to query maritime rules (COLREGs) and learn from human oversight. Using the ILP system PyGol, we demonstrate the learning of COLREG Rule 13 for overtaking situations from discretised bearing data, and further explore the learning of an exception to Rule 15 for crossing situations through examples inspired by case law. These results show the potential for interpretable, legally compliant decision-making and lay the groundwork for learning more complex rules in dynamic maritime environments.
KW - autonomy
KW - inductive logic programming
KW - machine learning
KW - Maritime law
UR - https://www.scopus.com/pages/publications/105029539681
U2 - 10.23919/OCEANS59106.2025.11245019
DO - 10.23919/OCEANS59106.2025.11245019
M3 - Chapter in a published conference proceeding
AN - SCOPUS:105029539681
T3 - Oceans Conference Record (IEEE)
SP - 1
EP - 8
BT - OCEANS 2025 - Great Lakes, OCEANS 2025
PB - IEEE
CY - U. S. A.
T2 - OCEANS 2025 - Great Lakes, OCEANS 2025
Y2 - 29 September 2025 through 2 October 2025
ER -