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Low-Cost Vision Based Autonomous Underwater Vehicle for Abyssal Ocean Ecosystem Research

dc.contributor.authorIscar Ruland, Eduardo Alexander
dc.date.accessioned2020-05-08T14:37:14Z
dc.date.availableNO_RESTRICTION
dc.date.available2020-05-08T14:37:14Z
dc.date.issued2020
dc.date.submitted2020
dc.identifier.urihttps://hdl.handle.net/2027.42/155225
dc.description.abstractThe oceans have a major impact on the planet: they store 28% of the CO 2 pro- duced by humans, they act as the world’s thermal damper for temperature changes, and more than 17, 000 species call the deep oceans their home. Scientific drivers, like climate change, and commercial applications, like deep sea fisheries and underwater mining, are pushing the need to know more about oceans at depths beyond 1000 meters. However, the high cost associated with autonomous underwater vehicles (AUVs) capable of operating beyond the depth of 1000 meters has limited the study of the deep ocean. Traditional AUVs used for deep-sea navigation are large and typically weigh up- wards of 1000-kgs, thus requiring careful planning before deployment and multi- person teams to operate. This thesis proposes the use of a new vehicle design based around a low-cost oceanographic glass sphere as the main pressure enclosure to reduce its size and cost while maintaining the ability for deep-sea operation. This novel housing concept, together with a minimal sensor suite, enables environmental research at depths previously inaccessible at this price point. The key characteristic that enables the cost reduction of this platform is the removal of the Doppler velocity log (DVL) sensor, which is replaced by optical cameras. Cameras allow the vehicle to estimate its motion in the water, but also enable scientific applications such as identification of habitat types or population density estimation of benthic species. After each survey, images can be further processed to produce full, dense 3D models of the survey area. While underwater optical cameras are frequently placed inside pressure housings behind flat or domed viewports and used for visual navigation or 3D reconstructions, the underlying assumptions for those algorithms do not hold in the underwater domain. Refraction at the housing viewport, together with wavelength-dependent attenuation of light in water, render the ubiquitous pinhole camera model invalid. This thesis presents a quantitative evaluation of the errors introduced by underwater effects for 3D reconstruction applications, comparing low- and high-cost camera systems to quantify the trade-off between equipment cost and performance. Although the distortion effects created by underwater refraction of light have been extensively studied for more traditional viewports, the novel design proposed necessitates new research into modeling the lensing effect of this off-axis domed viewport. A novel calibration method is presented that explicitly models the effect of the glass interface on image formation based on the characterization of optical distortions. The method is capable of accurately finding the position of the camera within the dome and further enables the use of deconvolution to improve the quality of the taken image. Finally, this thesis presents the validation of the designed vehicle for optical surveying tasks and introduces a end-to-end ocean mapping pipeline to streamline AUV deployments, enabling efficient use of time and resources.
dc.language.isoen_US
dc.subjectLow-cost
dc.subjectAutonomous Underwater Vehicle
dc.titleLow-Cost Vision Based Autonomous Underwater Vehicle for Abyssal Ocean Ecosystem Research
dc.typeThesis
dc.description.thesisdegreenamePhDen_US
dc.description.thesisdegreedisciplineNaval Architecture & Marine Engineering
dc.description.thesisdegreegrantorUniversity of Michigan, Horace H. Rackham School of Graduate Studies
dc.contributor.committeememberJohnson-Roberson, Matthew Kai
dc.contributor.committeememberShorter, K Alex
dc.contributor.committeememberSinger, David Jacob
dc.contributor.committeememberSun, Jing
dc.subject.hlbsecondlevelNaval Architecture and Marine Engineering
dc.subject.hlbtoplevelEngineering
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/155225/1/eiscar_1.pdf
dc.identifier.orcid0000-0003-3052-6743
dc.identifier.name-orcidIscar Ruland, Eduardo; 0000-0003-3052-6743en_US
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


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