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dc.contributor.authorGrøtli, Esten Ingar
dc.contributor.authorBjerkeng, Magnus Christian
dc.contributor.authorRundtop, Per
dc.contributor.authorVagia, Marialena
dc.contributor.authorBakkevig, Fredrik
dc.contributor.authorTranseth, Aksel Andreas
dc.date.accessioned2017-12-04T07:14:57Z
dc.date.available2017-12-04T07:14:57Z
dc.date.created2017-12-01T14:00:36Z
dc.date.issued2017
dc.identifier.citationOCEANS, 2017, pp 5nb_NO
dc.identifier.issn0197-7385
dc.identifier.urihttp://hdl.handle.net/11250/2468853
dc.description.abstractSeveral design methods and principles have been proposed in the literature in order to guide the design of autonomous operations. Putting the required efforts into learning and using the methods is a daunting task, and experiences have shown that the use of methods meant to the help the design process are often ignored. The reason could be that the design guidelines are too complex and contain information that is not relevant for the project at hand, and that there is no easy way to distinguish what is important from what is not. In this article, we propose a canvas as a tool to support the use of Autonomous Job Analysis (AJA). The authors have previously developed AJA as a structured method for designing an autonomous operation by breaking it down in to sub-operations in order to reveal challenges, needs and limitations regarding autonomous behavior. The canvas contains the categories of the AJA method on a single page - the canvas - and each category is supported with questions to be asked during the design procedure, as well as example answers. We will describe the AJA canvas in detail, and show how it can be applied to design an autonomous operation for inspection of the net of a sea based fish farm using an underwater vehicle.
dc.language.isoengnb_NO
dc.titleCanvas as a Design Tool for Autonomous Operations: : With application to net inspection of a sea based fish farm using an underwater vehiclenb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersion
dc.source.pagenumber5nb_NO
dc.source.journalOCEANSnb_NO
dc.identifier.doi10.1109/OCEANSE.2017.8084583
dc.identifier.cristin1521632
dc.relation.projectNorges forskningsråd: 237790nb_NO
cristin.unitcode7401,90,23,0
cristin.unitcode7566,3,0,0
cristin.unitcode7401,0,0,0
cristin.unitnameAnvendt kybernetikk
cristin.unitnameHavbruksteknologi
cristin.unitnameStiftelsen SINTEF
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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