Public defence in Automation, Systems and Control Engineering, M.Sc.(Tech.) Andrei Sandru

The title of the thesis: Sea-ice field analysis in polar regions for smart ships 

Thesis defender: Andrei Sandru
Opponent: Prof. Tor Arne Johansen, NTNU, Norway
Custos: Prof. Arto Visala, Aalto University School of Electrical Engineering

Due of 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, 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. 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. Last, 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 important challenges, since there are no reliable ground-points available, and almost no static targets.

Key words: machine vision, sea ice, lidar, sensor fusion, mapping

Thesis available for public display 7 days prior to the defence at Aaltodoc.