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Formulating layered adjustable autonomy for unmanned aerial vehicles

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dc.citedby39
dc.contributor.authorMostafa S.A.en_US
dc.contributor.authorAhmad M.S.en_US
dc.contributor.authorMustapha A.en_US
dc.contributor.authorMohammed M.A.en_US
dc.contributor.authorid37036085800en_US
dc.contributor.authorid56036880900en_US
dc.contributor.authorid57200530694en_US
dc.contributor.authorid57192089894en_US
dc.date.accessioned2023-05-29T06:40:04Z
dc.date.available2023-05-29T06:40:04Z
dc.date.issued2017
dc.descriptionControl theory; Hardware; Machinery; Multi agent systems; Unmanned aerial vehicles (UAV); Vehicles; Adjustable autonomy; Autonomous systems; Autonomous unmanned aerial vehicles; Autonomy levels; Computing machinery; Design/methodology/approach; Multi dimensional; Software and hardwares; Autonomous agentsen_US
dc.description.abstractPurpose: The purpose of this paper is to propose a layered adjustable autonomy (LAA) as a dynamically adjustable autonomy model for a multi-agent system. It is mainly used to efficiently manage humans� and agents� shared control of autonomous systems and maintain humans� global control over the agents. Design/methodology/approach: The authors apply the LAA model in an agent-based autonomous unmanned aerial vehicle (UAV) system. The UAV system implementation consists of two parts: software and hardware. The software part represents the controller and the cognitive, and the hardware represents the computing machinery and the actuator of the UAV system. The UAV system performs three experimental scenarios of dance, surveillance and search missions. The selected scenarios demonstrate different behaviors in order to create a suitable test plan and ensure significant results. Findings: The results of the UAV system tests prove that segregating the autonomy of a system as multi-dimensional and adjustable layers enables humans and/or agents to perform actions at convenient autonomy levels. Hence, reducing the adjustable autonomy drawbacks of constraining the autonomy of the agents, increasing humans� workload and exposing the system to disturbances. Originality/value: The application of the LAA model in a UAV manifests the significance of implementing dynamic adjustable autonomy. Assessing the autonomy within three phases of agents run cycle (task-selection, actions-selection and actions-execution) is an original idea that aims to direct agents� autonomy toward performance competency. The agents� abilities are well exploited when an incompetent agent switches with a more competent one. � 2017, � Emerald Publishing Limited.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1108/IJICC-02-2017-0013
dc.identifier.epage450
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85033696570
dc.identifier.spage430
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85033696570&doi=10.1108%2fIJICC-02-2017-0013&partnerID=40&md5=e16fec35ef7a04210156f96aa322fd72
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23391
dc.identifier.volume10
dc.publisherEmerald Group Publishing Ltd.en_US
dc.sourceScopus
dc.sourcetitleInternational Journal of Intelligent Computing and Cybernetics
dc.titleFormulating layered adjustable autonomy for unmanned aerial vehiclesen_US
dc.typeArticleen_US
dspace.entity.typePublication
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