Sea-ice field analysis in polar regions for smart ships

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School of Electrical Engineering | Doctoral thesis (article-based) | Defence date: 2025-09-05
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Authors

Date

2025

Department

Sähkötekniikan ja automaation laitos
Department of Electrical Engineering and Automation

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Mcode

Degree programme

Language

en

Pages

79 + app. 53

Series

Aalto University publication series Doctoral Theses, 155/2025

Abstract

Due to climate change, Arctic and Antarctic regions have experienced a diminishing sea-ice extent during the last decades. This situation poses both a risk factor for environmental disasters (e.g., loss of fauna, increasing sea levels), yet at the same time it presents new opportunities for ship operations (e.g., new and more efficient routes for cargo transit, research and tourism). However, the navigation or operation in ice-infested waters continues to pose a challenge, and detailed information about the sea-ice conditions is essential for navigation, to avoid in-water hazards (e.g., ice ridges, compression zones), but also to optimize parameters such as transit time and fuel consumption. In this research, traditional machine vision methods are used to develop an accurate sea-ice field analysis process by means of vision-based systems, capable of producing data describing local ice conditions such as concentration, sea-ice floe sizes and distribution. To support the orthorectification (i.e., obtaining a virtual bird’s eye view) and photogrammetry processes, a highly accurate method for attitude estimation from the horizon line is introduced, by means of a single monocular camera or through a visual-inertial sensor fusion. Then, methods for mapping highly dynamic environments using a laser scanner (LiDAR) were successfully implemented, to produce 3D point-cloud maps of the ice field in Antarctic conditions. Lastly, sensor fusion is used to produce highly detailed 2D maps of the sea-ice fields. These maps have been used so far in developing ship-ice interaction simulation models and represent the first attempt at digitizing and mapping sea-ice fields from imagery and other sensor data collected onboard a ship with decimetre-level accuracy. Additionally, during the study two experimental setups have been integrated, programmed, and instrumented onboard S.A. Agulhas II, to collect the required full-scale research data during various voyages to the Antarctic waters. The study aims at expanding the maritime industry’s knowledge and capabilities in ice-covered waters, by developing and improving algorithms for sea-ice field analysis and mapping using machine vision cameras and LiDARs. Such environments present real challenges, since there are no reliable ground-points available, and almost no static targets. Furthermore, the algorithms are implemented and evaluated in small- and full-scale real systems, not relying on simulators. These algorithms and methods support the automation of sea-ice monitoring, safe and efficient (semi- ) autonomous navigation in ice-covered waters, as well as the development of simulation models for ship-ice interaction.

Description

Supervising professor

Visala, Arto, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland

Thesis advisor

Kujala, Pentti, Prof., Aalto University, Department of Energy and Mechanical Engineering, Finland
Vainio, Mika, D.Sc., Aalto University, Department of Electrical Engineering and Automation, Finland

Keywords

sensors, sensor fusion, machine vision, lidar, situational awareness, sea ice

Other note

Parts

  • [Publication 1]: Andrei Sandru, Heikki Hyyti, Arto Visala, and Pentti Kujala. A Complete Process For Shipborne Sea-Ice Field Analysis Using Machine Vision. In IFAC-PapersOnLine, 53, 2, 14539–14545, 7 pages, , November 2020.
    Full text in Acris/Aaltodoc: https://urn.fi/URN:NBN:fi:aalto-202105196833
    DOI: 10.1016/j.ifacol. 2020.12.1458 View at publisher
  • [Publication 2]: Andrei Sandru, Arto Visala, and Pentti Kujala. Shipborne sea-ice field mapping using a LiDAR. In 2021 IEEE/RSJ International conference on Intelligent Robots and Systems (IROS), 8 pages, December 2021.
    Full text in Acris/Aaltodoc: https://urn.fi/URN:NBN:fi:aalto-202203032045
    DOI: 10.1109/IROS51168. 2021.9636275 View at publisher
  • [Publication 3]: Andrei Sandru, Pentti Kujala, and Arto Visala. Horizon detection and tracking in sea-ice conditions using machine vision. In IFACPapersOnLine, 56, 2, 6724–6730, 7 pages, July 2023.
    Full text in Acris/Aaltodoc: https://urn.fi/URN:NBN:fi:aalto-202402142400
    DOI: 10.1016/j.ifacol.2023.10.377 View at publisher
  • [Publication 4]: A. Sandru, A. Visala, P. Kujala. Sea-ice mapping and digitization in Antarctic waters using a shipborne monocular camera. Cold Regions Science and Technology, 239, 104563, 12 pages, , June 2025.
    Full text in Acris/Aaltodoc: https://urn.fi/URN:NBN:fi:aalto-202508206595
    DOI: 10.1016/j.coldregions. 2025.104563 View at publisher
  • [Publication 5]: A. Sandru, H. Hyyti, A. Visala. Horizon detection and tracking through visual-inertial fusion in polar regions. Submitted to IEEE Sensors Journal, 6 pages, May 2025

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https://urn.fi/URN:ISBN:978-952-64-2680-8

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[diss] Sähkötekniikan korkeakoulu / ELEC