Talking with robots about objects a system-level evaluation in HRI

We present the design process, realization and evaluation of a robot system for nteractive object learning. The system-oriented evaluation, in particular, addresses an open problem for the evaluation of systems, where overall user satisfaction depends not only on the performance of the parts, but al...

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Bibliographic Details
Published in:2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI) pp. 479 - 486
Main Authors: Peltason, Julia, Riether, Nina, Wrede, Britta, Lütkebohle, Ingo
Format: Conference Proceeding
Language:English
Published: New York, NY, USA ACM 05.03.2012
IEEE
Series:ACM Conferences
Subjects:
Atmospheric measurements
Computer systems organization > Embedded and cyber-physical systems > Robotics
Computing methodologies > Artificial intelligence > Control methods > Robotic planning
Computing methodologies > Artificial intelligence > Natural language processing
Computing methodologies > Artificial intelligence > Planning and scheduling > Robotic planning
General and reference > Cross-computing tools and techniques > Measurement
General and reference > Cross-computing tools and techniques > Metrics
Human-robot interaction
Humans
object learning
Particle measurements
Robots
social robotics
Speech recognition
USA Councils
object learning
human-robot interaction
social robotics
ISBN:145031063X, 9781450310635
ISSN:2167-2121
Online Access:Get full text
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Summary:We present the design process, realization and evaluation of a robot system for nteractive object learning. The system-oriented evaluation, in particular, addresses an open problem for the evaluation of systems, where overall user satisfaction depends not only on the performance of the parts, but also on their combination, and on user behavior. Based on the PARADISE method known from spoken dialog systems, we have defined and applied internal and external metrics for fine-grained and largely automatable identification of such relationships. Through evaluation with n=28 subjects, indicator functions explaining up to 55% of variation in several satisfaction metrics were found. Furthermore, we demonstrate that the system's interaction style reduces the need for instruction and successfully recovers partial failures.
ISBN:145031063X
9781450310635
ISSN:2167-2121
DOI:10.1145/2157689.2157841