Experimental Monitoring of Sea Ice Using Unmanned Aerial Systems

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 th...

Full description

Bibliographic Details
Main Author: Flåten, Andreas L.
Other Authors: Imsland, Lars, Albert, Anders, Leira, Frederik Stendahl
Format: Master Thesis
Language:English
Published: NTNU 2015
Subjects:
Online Access:http://hdl.handle.net/11250/2352540
id ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2352540
record_format openpolar
spelling ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/2352540 2023-05-15T14:55:21+02:00 Experimental Monitoring of Sea Ice Using Unmanned Aerial Systems Flåten, Andreas L. Imsland, Lars Albert, Anders Leira, Frederik Stendahl 2015 http://hdl.handle.net/11250/2352540 eng eng NTNU ntnudaim:12701 http://hdl.handle.net/11250/2352540 Kybernetikk og robotikk Master thesis 2015 ftntnutrondheimi 2019-09-17T06:51:06Z 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. Master Thesis Arctic Sea ice Svalbard NTNU Open Archive (Norwegian University of Science and Technology) Arctic Svalbard
institution Open Polar
collection NTNU Open Archive (Norwegian University of Science and Technology)
op_collection_id ftntnutrondheimi
language English
topic Kybernetikk og robotikk
spellingShingle Kybernetikk og robotikk
Flåten, Andreas L.
Experimental Monitoring of Sea Ice Using Unmanned Aerial Systems
topic_facet Kybernetikk og robotikk
description 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.
author2 Imsland, Lars
Albert, Anders
Leira, Frederik Stendahl
format Master Thesis
author Flåten, Andreas L.
author_facet Flåten, Andreas L.
author_sort Flåten, Andreas L.
title Experimental Monitoring of Sea Ice Using Unmanned Aerial Systems
title_short Experimental Monitoring of Sea Ice Using Unmanned Aerial Systems
title_full Experimental Monitoring of Sea Ice Using Unmanned Aerial Systems
title_fullStr Experimental Monitoring of Sea Ice Using Unmanned Aerial Systems
title_full_unstemmed Experimental Monitoring of Sea Ice Using Unmanned Aerial Systems
title_sort experimental monitoring of sea ice using unmanned aerial systems
publisher NTNU
publishDate 2015
url http://hdl.handle.net/11250/2352540
geographic Arctic
Svalbard
geographic_facet Arctic
Svalbard
genre Arctic
Sea ice
Svalbard
genre_facet Arctic
Sea ice
Svalbard
op_relation ntnudaim:12701
http://hdl.handle.net/11250/2352540
_version_ 1766327151171207168