Alexandros Troupiotis-Kapeliaris

University of the Aegean · Department of Product and Systems Design Engineering

Recent advancements in sensor and tracking technologies have facilitated the real-time tracking of marine vessels as they traverse the oceans. As a result, there is an increasing demand to analyze these datasets to derive insights into vessel movement patterns and to investigate activities occurring within specific spatial and temporal contexts. Th...

The “Aegean Ro-boat Race” is an international university level competition, challenging teams to design and develop innovative autonomous robotic systems that can perform at sea in real world conditions. This is an innovation race amongst universities, but with the support of industry, that merges visionary thinking from different fields to solve p...

The task of accurately forecasting the trajectory of a vessel, and in general a moving object operating in free space until its destination remains an open challenge. This paper addresses this problem by describing an unsupervised data-driven framework for short and extended horizon forecasts, from the perspectives of data mining and machine learni...

In this paper, we introduce a publicly available real-world dataset collected during the Aegean Ro-Boat Race 2023, which took place at the University of the Aegean in Syros, Greece. The Aegean Ro-boat Race represents an international competition at the university level, challenging teams to innovate and develop autonomous marine robotic systems cap...

Density maps support a bird’s eye view of vessel traffic, through providing an overview of vessel behavior, either at a regional or global scale in a given timeframe. However, any inaccuracies in the underlying data, due to sensor noise or other factors, evidently lead to erroneous interpretations and misleading visualizations. In this work, we pro...

Sudden changes in a vessel's path are common, complicating efforts to predict future behavior. In this work, we leverage existing traffic to develop an algorithm that makes informed trajectory predictions. Our method begins with analyzing historical maritime traffic using AIS data from vessels in southern New England. This analysis culminates in cr...

Digital twins are computational models that replicate the structure, behaviour and overall characteristics of a physical asset in the digital world. In the maritime domain, conventional approaches have relied on mathematical modeling (e.g., linearised equations of motion) and heavy computations for estimating ship resistance and propulsion, seakeep...

Unlike land routing, sea navigation takes place in "free-space", not constrained to strict road networks. To ensure safety of passage, mariners tend to use commonly traveled routes. Nautical and routing charts provide information regarding dangers to navigation and shipping routes and distances between major ports, however they are often outdated o...