Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Underwater Positioning of an ROV Using Side-Mounted Sonars
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Unmanned vehicles being used more and more for tasks that need to be done in environ- ments that are hard to access, or dangerous for humans. Because the vehicles are unmanned they need some way of conveying information to the operator about where it is located. In some cases visual feedback to the operator might be enough, but in environments with low visibility other techniques are required.

This thesis will address the issue of localization in an underwater environment by means of side-scan sonars and an inertial measurement unit (IMU). It will explore whether it is possible to localize a remotely operated vehicle (ROV) in a known environment by fusing data from the different sensors.

A particle filter is applied to the translational motion of the ROV and an extended kalman filter is used to estimate the vehicles attitude. The focus of the thesis lies in statistical mod- eling and simulation of the ROV and its sensors rather than in validation and testing in the physical realm.

Results show that a particle filter localization is plausible in environments given varied enough readings. For cases where measurements are similar, such as close to the floor of a pool the filter tends to diverge. 

Place, publisher, year, edition, pages
2014. , 55 p.
Keyword [en]
localization, particle filters, ROV
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-119096ISRN: LiTH-ISY-EX--14/4749--SEOAI: oai:DiVA.org:liu-119096DiVA: diva2:818710
Subject / course
Automatic Control
Supervisors
Examiners
Available from: 2015-06-15 Created: 2015-06-09 Last updated: 2016-08-31Bibliographically approved

Open Access in DiVA

fulltext(5600 kB)