The Effect of Robot Appearance Types and Task Types on Service Evaluation of a Robot
Pages 223 - 224
Abstract
Robot's appearance types could be classified into two types: human-oriented and product-oriented. Human-oriented robot resembles human's appearance whereas product-oriented robot is an intelligent product that robotic technologies are integrated into existing product. In this study, we investigated the impact of two robot appearance types and two task types on service evaluation of a robot. We executed a 2 (robot appearance types: human-oriented vs. product-oriented) x 2 (robot task types: social context vs. task-oriented context) mixed-methods experiment design (N=48). In the case of social context, people evaluated the service provided by a human-oriented robot better than by a product-oriented robot while in the case of task-oriented context, they evaluated the service provided by a product-oriented robot more positively than by a human-oriented robot. Implications for the design of human-robot interaction are discussed.
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Published In
March 2015
336 pages
ISBN:9781450333184
DOI:10.1145/2701973
- General Chairs:
- Julie A. Adams,
- William Smart,
- Program Chairs:
- Bilge Mutlu,
- Leila Takayama
Copyright © 2015 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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- SIGAI: ACM Special Interest Group on Artificial Intelligence
- RA: IEEE Robotics and Automation Society
- SIGCHI: ACM Special Interest Group on Computer-Human Interaction
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Association for Computing Machinery
New York, NY, United States
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Published: 02 March 2015
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HRI '15: ACM/IEEE International Conference on Human-Robot Interaction
March 2 - 5, 2015
Oregon, Portland, USA
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HRI'15 Extended Abstracts Paper Acceptance Rate 92 of 102 submissions, 90%;
Overall Acceptance Rate 192 of 519 submissions, 37%
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