DocumentCode :
138482
Title :
Investigating human perceptions of robot capabilities in remote human-robot team tasks based on first-person robot video feeds
Author :
Canning, Cody ; Donahue, Thomas J. ; Scheutz, Matthias
Author_Institution :
Dept. of Comput. Sci., Tufts Univ., Medford, MA, USA
fYear :
2014
fDate :
14-18 Sept. 2014
Firstpage :
4354
Lastpage :
4361
Abstract :
It is well-known that a robot´s appearance and its observable behavior can affect a human interactant´s perceptions of the robot´s capabilities and propensities in settings where humans and robots are co-located; for remote interactions the specific effects are less clear. Here, we use a remote interaction setting to investigate possible effects of simulated versus real first-person robot video feeds. The first experiment uses subject-level comparisons of the two video conditions in a multi-robot setting while the second and third experiments focus on a single robot, single video condition using a larger population (via Amazon Mechanical Turk) to study between-subjects effects. The latter experiments also probe the effects of robot appearance, video feed type, and stake humans have in the task. We observe a complex interplay between interaction, robot appearance, and video feed type as they affect perceived collaboration, utility, competence, and warmth of the robot.
Keywords :
cameras; human-robot interaction; multi-robot systems; robot vision; video signal processing; Amazon Mechanical Turk; first-person robot video feeds; human interactant perceptions; observable behavior; real first-person robot video feeds; remote human-robot team tasks; remote interactions; robot appearance; robot capabilities; subject-level comparisons; video conditions; Collaboration; Feeds; Robot vision systems; Webcams;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on
Conference_Location :
Chicago, IL
Type :
conf
DOI :
10.1109/IROS.2014.6943178
Filename :
6943178
Link To Document :
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