A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management
A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive dem...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hocraffer, Amy [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017transfer abstract |
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| Schlagwörter: |
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| Umfang: |
15 |
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| Übergeordnetes Werk: |
Enthalten in: Effects of external electric field on the optical and electronic properties of blue phosphorene nanoribbons: A DFT study - Ospina, D.A. ELSEVIER, 2017, human factors in technology and society, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:58 ; year:2017 ; pages:66-80 ; extent:15 |
| Links: |
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| DOI / URN: |
10.1016/j.apergo.2016.05.011 |
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ELV030756014 |
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| 520 | |a A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. | ||
| 520 | |a A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. | ||
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10.1016/j.apergo.2016.05.011 doi GBVA2017019000025.pica (DE-627)ELV030756014 (ELSEVIER)S0003-6870(16)30098-9 DE-627 ger DE-627 rakwb eng 330 330 DE-600 530 VZ 600 670 530 VZ 51.00 bkl Hocraffer, Amy verfasserin aut A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management 2017transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. Swarm Elsevier Unmanned aerial vehicle (UAV) Elsevier Human-system interface Elsevier Human-robot interaction Elsevier Human-swarm interaction Elsevier Human factors Elsevier Multi-robot systems Elsevier Nam, Chang S. oth Enthalten in Elsevier Science Ospina, D.A. ELSEVIER Effects of external electric field on the optical and electronic properties of blue phosphorene nanoribbons: A DFT study 2017 human factors in technology and society Amsterdam [u.a.] (DE-627)ELV020430949 volume:58 year:2017 pages:66-80 extent:15 https://doi.org/10.1016/j.apergo.2016.05.011 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 51.00 Werkstoffkunde: Allgemeines VZ AR 58 2017 66-80 15 045F 330 |
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10.1016/j.apergo.2016.05.011 doi GBVA2017019000025.pica (DE-627)ELV030756014 (ELSEVIER)S0003-6870(16)30098-9 DE-627 ger DE-627 rakwb eng 330 330 DE-600 530 VZ 600 670 530 VZ 51.00 bkl Hocraffer, Amy verfasserin aut A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management 2017transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. Swarm Elsevier Unmanned aerial vehicle (UAV) Elsevier Human-system interface Elsevier Human-robot interaction Elsevier Human-swarm interaction Elsevier Human factors Elsevier Multi-robot systems Elsevier Nam, Chang S. oth Enthalten in Elsevier Science Ospina, D.A. ELSEVIER Effects of external electric field on the optical and electronic properties of blue phosphorene nanoribbons: A DFT study 2017 human factors in technology and society Amsterdam [u.a.] (DE-627)ELV020430949 volume:58 year:2017 pages:66-80 extent:15 https://doi.org/10.1016/j.apergo.2016.05.011 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 51.00 Werkstoffkunde: Allgemeines VZ AR 58 2017 66-80 15 045F 330 |
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10.1016/j.apergo.2016.05.011 doi GBVA2017019000025.pica (DE-627)ELV030756014 (ELSEVIER)S0003-6870(16)30098-9 DE-627 ger DE-627 rakwb eng 330 330 DE-600 530 VZ 600 670 530 VZ 51.00 bkl Hocraffer, Amy verfasserin aut A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management 2017transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. Swarm Elsevier Unmanned aerial vehicle (UAV) Elsevier Human-system interface Elsevier Human-robot interaction Elsevier Human-swarm interaction Elsevier Human factors Elsevier Multi-robot systems Elsevier Nam, Chang S. oth Enthalten in Elsevier Science Ospina, D.A. ELSEVIER Effects of external electric field on the optical and electronic properties of blue phosphorene nanoribbons: A DFT study 2017 human factors in technology and society Amsterdam [u.a.] (DE-627)ELV020430949 volume:58 year:2017 pages:66-80 extent:15 https://doi.org/10.1016/j.apergo.2016.05.011 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 51.00 Werkstoffkunde: Allgemeines VZ AR 58 2017 66-80 15 045F 330 |
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10.1016/j.apergo.2016.05.011 doi GBVA2017019000025.pica (DE-627)ELV030756014 (ELSEVIER)S0003-6870(16)30098-9 DE-627 ger DE-627 rakwb eng 330 330 DE-600 530 VZ 600 670 530 VZ 51.00 bkl Hocraffer, Amy verfasserin aut A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management 2017transfer abstract 15 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. Swarm Elsevier Unmanned aerial vehicle (UAV) Elsevier Human-system interface Elsevier Human-robot interaction Elsevier Human-swarm interaction Elsevier Human factors Elsevier Multi-robot systems Elsevier Nam, Chang S. oth Enthalten in Elsevier Science Ospina, D.A. ELSEVIER Effects of external electric field on the optical and electronic properties of blue phosphorene nanoribbons: A DFT study 2017 human factors in technology and society Amsterdam [u.a.] (DE-627)ELV020430949 volume:58 year:2017 pages:66-80 extent:15 https://doi.org/10.1016/j.apergo.2016.05.011 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 51.00 Werkstoffkunde: Allgemeines VZ AR 58 2017 66-80 15 045F 330 |
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Effects of external electric field on the optical and electronic properties of blue phosphorene nanoribbons: A DFT study |
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Effects of external electric field on the optical and electronic properties of blue phosphorene nanoribbons: A DFT study |
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a meta-analysis of human-system interfaces in unmanned aerial vehicle (uav) swarm management |
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A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management |
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A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. |
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A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. |
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A meta-analysis was conducted to systematically evaluate the current state of research on human-system interfaces for users controlling semi-autonomous swarms composed of groups of drones or unmanned aerial vehicles (UAVs). UAV swarms pose several human factors challenges, such as high cognitive demands, non-intuitive behavior, and serious consequences for errors. This article presents findings from a meta-analysis of 27 UAV swarm management papers focused on the human-system interface and human factors concerns, providing an overview of the advantages, challenges, and limitations of current UAV management interfaces, as well as information on how these interfaces are currently evaluated. In general allowing user and mission-specific customization to user interfaces and raising the swarm’s level of autonomy to reduce operator cognitive workload are beneficial and improve situation awareness (SA). It is clear more research is needed in this rapidly evolving field. |
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A meta-analysis of human-system interfaces in unmanned aerial vehicle (UAV) swarm management |
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