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Human to robot demonstrations of routine home tasks: exploring the role of the robot's feedback
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ACM/IEEE International Conference on Human-Robot Interaction archive
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction table of contents
Amsterdam, The Netherlands
SESSION: Technical papers table of contents
Pages 177-184  
Year of Publication: 2008
ISBN:978-1-60558-017-3
Authors
Nuno Otero  University of Hertfordshire, Hatfield, United Kingdom
Aris Alissandrakis  University of Hertfordshire, Hatfield, United Kingdom
Kerstin Dautenhahn  University of Hertfordshire, Hatfield, United Kingdom
Chrystopher Nehaniv  University of Hertfordshire, Hatfield, United Kingdom
Dag Sverre Syrdal  University of Hertfordshire, Hatfield, United Kingdom
Kheng Lee Koay  University of Hertfordshire, Hatfield, United Kingdom
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this paper, we explore some conceptual issues, relevant for the design of robotic systems aimed at interacting with humans in domestic environments. More specifically, we study the role of the robot's feedback (positive or negative acknowledgment of understanding) on a human teacher's demonstration of a routine home task (laying a table). Both the human and the system's perspectives are considered in the analysis and discussion of results from a human-robot user study, highlighting some important conceptual and practical issues. These include the lack of explicitness and consistency on people's demonstration strategies. Furthermore, we discuss the need to investigate design strategies to elicit people's knowledge about the task and also successfully advertize the robot's abilities in order to promote people's ability to provide appropriate demonstrations.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Nuno Otero: colleagues
Aris Alissandrakis: colleagues
Kerstin Dautenhahn: colleagues
Chrystopher Nehaniv: colleagues
Dag Sverre Syrdal: colleagues
Kheng Lee Koay: colleagues