Change search
ReferencesLink to record
Permanent link

Direct link
Relocating Underwater Features Autonomously Using Sonar-Based SLAM
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0002-7796-1438
2013 (English)In: IEEE Journal of Oceanic Engineering, ISSN 0364-9059, E-ISSN 1558-1691, Vol. 38, no 3, 500-513 p.Article in journal (Refereed) Published
Abstract [en]

This paper describes a system for reacquiring features of interest in a shallow-water ocean environment, using autonomous underwater vehicles (AUVs) equipped with low-cost sonar and navigation sensors. In performing mine countermeasures, it is critical to enable AUVs to navigate accurately to previously mapped objects of interest in the water column or on the seabed, for further assessment or remediation. An important aspect of the overall system design is to keep the size and cost of the reacquisition vehicle as low as possible, as it may potentially be destroyed in the reacquisition mission. This low-cost requirement prevents the use of sophisticated AUV navigation sensors, such as a Doppler velocity log (DVL) or an inertial navigation system (INS). Our system instead uses the Proviewer 900-kHz imaging sonar from Blueview Technologies, which produces forward-looking sonar (FLS) images at ranges up to 40 m at approximately 4 Hz. In large volumes, it is hoped that this sensor can be manufactured at low cost. Our approach uses a novel simultaneous localization and mapping (SLAM) algorithm that detects and tracks features in the FLS images to renavigate to a previously mapped target. This feature-based navigation (FBN) system incorporates a number of recent advances in pose graph optimization algorithms for SLAM. The system has undergone extensive field testing over a period of more than four years, demonstrating the potential for the use of this new approach for feature reacquisition. In this report, we review the methodologies and components of the FBN system, describe the system's technological features, review the performance of the system in a series of extensive in-water field tests, and highlight issues for future research.

Place, publisher, year, edition, pages
IEEE Oceanic Engineering Society, 2013. Vol. 38, no 3, 500-513 p.
Keyword [en]
Marine navigation, marine vehicles, mobile robots, sensor fusion, simultaneous localization and mapping (SLAM), sonar detection, synthetic aperture sonar, underwater technology
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-126889DOI: 10.1109/JOE.2012.2235664ISI: 000321925500009ScopusID: 2-s2.0-84880570312OAI: diva2:642654

QC 20130822

Available from: 2013-08-22 Created: 2013-08-22 Last updated: 2016-02-12Bibliographically approved

Open Access in DiVA

fulltext(2068 kB)9 downloads
File information
File name FULLTEXT01.pdfFile size 2068 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopusIEEEXplore

Search in DiVA

By author/editor
Folkesson, John
By organisation
Centre for Autonomous Systems, CAS
In the same journal
IEEE Journal of Oceanic Engineering
Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 9 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 106 hits
ReferencesLink to record
Permanent link

Direct link