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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
Identifiers
URN: urn:nbn:se:kth:diva-126889DOI: 10.1109/JOE.2012.2235664ISI: 000321925500009Scopus ID: 2-s2.0-84880570312OAI: oai:DiVA.org:kth-126889DiVA: diva2:642654
Note

QC 20130822

Available from: 2013-08-22 Created: 2013-08-22 Last updated: 2017-12-06Bibliographically approved

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Folkesson, John

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