Experimental Monitoring of Sea Ice Using Unmanned Aerial Systems
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The exploration of arctic seas for offshore oil- and gas resources has received increasinginterest the past few years. Despite the recent dramatic fall in oil prices,estimates indicate that as much as 22% of the worlds remaining hydrocarbons arelocated in arctic areas. Thus it is unlikely that the arctic areas will go largelyuntouched the following decades. One of the main challenges of extracting hydrocarbonsin arctic areas is the abundance of sea ice that can cause damaging loads oninstallations. An important part of oil exploration in these areas is thus the abilityto manage potentially damaging sea ice. The current methods for ice managementinclude manned helicopters and other aircraft for detection together with ships tobreak up or drag away dangerous ice. The main objective of this thesis is to assessthe use of Unmanned Aerial Systems (UAS) to perform ice monitoring. An autonomousUnmanned Aerial System for ice detection and mapping using a thermalimaging sensor on a small fixed wing aircraft is proposed. The main contributionsof this thesis is a real-time Bayesian recursive algorithm for occupancy grid mapestimation representing sea ice. An expedition to Svalbard with several PhD andmaster students from NTNU was originally planned in April 2015, but this wascanceled in March due to time constraints among the participants. The expeditionwas a major source of inspiration for the methods developed, and an indoorlaboratory environment for on-board computer vision was developedusing the Robot Operating System (ROS) software framework. The setup includeda quadcopter with an on-board camera, and a motion capture system capable oftracking the pose of the quadcopter at 120 Hz. The laboratory setup was used totest much of the planned functionality for the Svalbard expedition. The developedcomputer vision based map estimation algorithm is capable of running in real time on an on-board computer. As a part ofthe preparation for the Svalbard excursion, a path planning framework developedby PhD student Anders Albert was successfully tested in the laboratory setup.The experimental results of the mapping algorithm were visually appealing, butcloser investigation revealed unsatisfactory accuracy. Using on-board navigationalsystems alone to perform real-time mapping did not yield sucient accuracy forpractical use. Sources of error and means to improve the results in further workwere investigated.