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Experimental Monitoring of Sea Ice Using Unmanned Aerial Systems

Flåten, Andreas L.
Master thesis
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URI
http://hdl.handle.net/11250/2352540
Date
2015
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  • Institutt for teknisk kybernetikk [2251]
Abstract
The exploration of arctic seas for offshore oil- and gas resources has received increasing

interest the past few years. Despite the recent dramatic fall in oil prices,

estimates indicate that as much as 22% of the worlds remaining hydrocarbons are

located in arctic areas. Thus it is unlikely that the arctic areas will go largely

untouched the following decades. One of the main challenges of extracting hydrocarbons

in arctic areas is the abundance of sea ice that can cause damaging loads on

installations. An important part of oil exploration in these areas is thus the ability

to manage potentially damaging sea ice. The current methods for ice management

include manned helicopters and other aircraft for detection together with ships to

break up or drag away dangerous ice. The main objective of this thesis is to assess

the use of Unmanned Aerial Systems (UAS) to perform ice monitoring. An autonomous

Unmanned Aerial System for ice detection and mapping using a thermal

imaging sensor on a small fixed wing aircraft is proposed. The main contributions

of this thesis is a real-time Bayesian recursive algorithm for occupancy grid map

estimation representing sea ice. An expedition to Svalbard with several PhD and

master students from NTNU was originally planned in April 2015, but this was

canceled in March due to time constraints among the participants. The expedition

was a major source of inspiration for the methods developed, and an indoor

laboratory environment for on-board computer vision was developed

using the Robot Operating System (ROS) software framework. The setup included

a quadcopter with an on-board camera, and a motion capture system capable of

tracking the pose of the quadcopter at 120 Hz. The laboratory setup was used to

test much of the planned functionality for the Svalbard expedition. The developed

computer vision based map estimation algorithm is capable of running in real time on an on-board computer. As a part of

the preparation for the Svalbard excursion, a path planning framework developed

by PhD student Anders Albert was successfully tested in the laboratory setup.

The experimental results of the mapping algorithm were visually appealing, but

closer investigation revealed unsatisfactory accuracy. Using on-board navigational

systems alone to perform real-time mapping did not yield sucient accuracy for

practical use. Sources of error and means to improve the results in further work

were investigated.
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NTNU

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