DocumentCode :
567315
Title :
Evaluating the applicability of current models of workload to peer-based human-robot teams
Author :
Harriott, Caroline E. ; Zhang, Tao ; Adams, Julie A.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Vanderbilt Univ. Nashville, Nashville, TN, USA
fYear :
2011
fDate :
8-11 March 2011
Firstpage :
45
Lastpage :
52
Abstract :
Human-Robot peer-based teams are evolving from a far-off possibility into a reality. Human Performance Moderator Functions (HPMFs) can be used to predict human behavior by incorporating the effects of internal and external influences such as fatigue and workload. The applicability of HPMFs to human-robot teams is not proven. The presented research focuses on determining the applicability of workload HPMFs in team tasks for first response mass casualty triage incidents between a Human-Human and a Human-Robot team. A model representing workload for each team was developed using IMPRINT Pro. The results from an empirical evaluation were compared to the model results. While significant differences between the two conditions were not found in all data, there was a general trend that workload in the human-robot condition was slightly lower than the workload experienced in the human-human condition. This trend was predicted by the IMPRINT Pro models. These results are the first to indicate that existing HPMFs can be applied to human-robot peer-based teams.
Keywords :
human factors; human-robot interaction; HPMF; IMPRINT Pro models; external influences; first response mass casualty triage incidents; human behavior prediction; human performance moderator functions; human-human team; human-robot peer-based teams; internal influences; peer-based human-robot teams; Heart rate variability; Humans; Pediatrics; Pollution measurement; Robots; Speech; human-performance modeling; human-robot peer-based teams;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Human-Robot Interaction (HRI), 2011 6th ACM/IEEE International Conference on
Conference_Location :
Lausanne
ISSN :
2167-2121
Print_ISBN :
978-1-4673-4393-0
Electronic_ISBN :
2167-2121
Type :
conf
Filename :
6281381
Link To Document :
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