Formulating layered adjustable autonomy for unmanned aerial vehicles
作者机构：Faculty of Computer Science and Information TechnologyUniversiti Tun Hussein Onn MalaysiaBatu PahatMalaysia College of Information TechnologyUniversiti Tenaga NasionalKajangMalaysia Planning and Follow Up DepartmentUniversity of AnbarAnbarIraq
出 版 物：《International Journal of Intelligent Computing and Cybernetics》 (智能计算与控制论国际期刊（英文）)
年 卷 期：2017年第10卷第4期
页 面：430-450页
核心收录：
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Unmanned aerial vehicle Multi-agent system Adjustable autonomy Autonomous agent
摘 要：Purpose–The purpose of this paper is to propose a layered adjustable autonomy(LAA)as a dynamically adjustable autonomy model for a multi-agent *** is mainly used to efficiently manage humans’and agents’shared control of autonomous systems and maintain humans’global control over the ***/methodology/approach–The authors apply the LAA model in an agent-based autonomous unmanned aerial vehicle(UAV)*** UAV system implementation consists of two parts:software and *** software part represents the controller and the cognitive,and the hardware represents the computing machinery and the actuator of the UAV *** UAV system performs three experimental scenarios of dance,surveillance and search *** selected scenarios demonstrate different behaviors in order to create a suitable test plan and ensure significant ***–The results of the UAV system tests prove that segregating the autonomy of a system as multidimensional and adjustable layers enables humans and/or agents to perform actions at convenient autonomy ***,reducing the adjustable autonomy drawbacks of constraining the autonomy of the agents,increasing humans’workload and exposing the system to ***/value–The application of the LAA model in a UAV manifests the significance of implementing dynamic adjustable *** the autonomy within three phases of agents run cycle(taskselection,actions-selection and actions-execution)is an original idea that aims to direct agents’autonomy toward performance *** agents’abilities are well exploited when an incompetent agent switches with a more competent one.
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