Achieving fluency through perceptual-symbol practice in human-robot collaboration

We have developed a cognitive architecture for robotic teammates based on the neuro-psychological principles of perceptual symbols and simulation, with the aim of attaining increased fluency in human-robot teams. An instantiation of this architecture was implemented on a robotic desk lamp, performin...

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Bibliographic Details
Published in:2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI) pp. 1 - 8
Main Authors: Hoffman, Guy, Breazeal, Cynthia
Format: Conference Proceeding
Language:English
Published: New York, NY, USA ACM 12.03.2008
IEEE
Series:ACM Conferences
Subjects:
Anticipation
Cognitive Architectures
Collaboration
Color
Computer systems organization > Embedded and cyber-physical systems > Robotics
Computing methodologies > Artificial intelligence > Control methods > Robotic planning
Computing methodologies > Artificial intelligence > Knowledge representation and reasoning
Computing methodologies > Artificial intelligence > Planning and scheduling > Robotic planning
Fluency
Human Subject Studies
Human-Robot Interaction
Humans
Perceptual Symbols
Robot kinematics
Robot sensing systems
Robotics
Speech
Teamwork
Theory of computation > Logic
human-robot interaction
human subject studies
perceptual symbols
cognitive architectures
teamwork
anticipation
robotics
fluency
ISBN:1605580171, 9781605580173
ISSN:2167-2121
Online Access:Get full text
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Summary:We have developed a cognitive architecture for robotic teammates based on the neuro-psychological principles of perceptual symbols and simulation, with the aim of attaining increased fluency in human-robot teams. An instantiation of this architecture was implemented on a robotic desk lamp, performing in a human-robot collaborative task. This paper describes initial results from a human-subject study measuring team efficiency and team fluency, in which the robot works on a joint task with untrained subjects. We find significant differences in a number of efficiency and fluency metrics, when comparing our architecture to a purely reactive robot with similar capabilities.
ISBN:1605580171
9781605580173
ISSN:2167-2121
DOI:10.1145/1349822.1349824