Abstract
Human's direct supervision on robot's erroneous behavior is crucial to enhance a robot intelligence for a 'flawless' human-robot interaction. Motivating humans to engage more actively for this purpose is however difficult. To alleviate such strain, this research proposes a novel approach, a growth and regression metaphoric interaction design inspired from human's communicative, intellectual, social competence aspect of developmental stages. We implemented the interaction design principle unto a conversational agent combined with a set of synthetic sensors. Within this context, we aim to show that the agent successfully encourages the online labeling activity in response to the faulty behavior of robots as a supervision process. The field study is going to be conducted to evaluate the efficacy of our proposal by measuring the annotation performance of real-time activity events in the wild. We expect to provide a more effective and practical means to supervise robot by real-time data labeling process for long-term usage in the human-robot interaction.
| Original language | English |
|---|---|
| Title of host publication | HRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction |
| Publisher | IEEE Computer Society |
| Pages | 646-647 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781538685556 |
| DOIs | |
| Publication status | Published - 2019 Mar 22 |
| Event | 14th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2019 - Daegu, Korea, Republic of Duration: 2019 Mar 11 → 2019 Mar 14 |
Publication series
| Name | ACM/IEEE International Conference on Human-Robot Interaction |
|---|---|
| Volume | 2019-March |
| ISSN (Electronic) | 2167-2148 |
Conference
| Conference | 14th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2019 |
|---|---|
| Country | Korea, Republic of |
| City | Daegu |
| Period | 19/3/11 → 19/3/14 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Human-Computer Interaction
- Electrical and Electronic Engineering
Cite this
}
Lifespan Design of Conversational Agent with Growth and Regression Metaphor for the Natural Supervision on Robot Intelligence. / Park, Chan Mi; Lee, Jung Yeon; Baek, Hyoung Woo; Lee, Hae Sung; Lee, Jee Hang; Kim, Jinwoo.
HRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction. IEEE Computer Society, 2019. p. 646-647 8673212 (ACM/IEEE International Conference on Human-Robot Interaction; Vol. 2019-March).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Lifespan Design of Conversational Agent with Growth and Regression Metaphor for the Natural Supervision on Robot Intelligence
AU - Park, Chan Mi
AU - Lee, Jung Yeon
AU - Baek, Hyoung Woo
AU - Lee, Hae Sung
AU - Lee, Jee Hang
AU - Kim, Jinwoo
PY - 2019/3/22
Y1 - 2019/3/22
N2 - Human's direct supervision on robot's erroneous behavior is crucial to enhance a robot intelligence for a 'flawless' human-robot interaction. Motivating humans to engage more actively for this purpose is however difficult. To alleviate such strain, this research proposes a novel approach, a growth and regression metaphoric interaction design inspired from human's communicative, intellectual, social competence aspect of developmental stages. We implemented the interaction design principle unto a conversational agent combined with a set of synthetic sensors. Within this context, we aim to show that the agent successfully encourages the online labeling activity in response to the faulty behavior of robots as a supervision process. The field study is going to be conducted to evaluate the efficacy of our proposal by measuring the annotation performance of real-time activity events in the wild. We expect to provide a more effective and practical means to supervise robot by real-time data labeling process for long-term usage in the human-robot interaction.
AB - Human's direct supervision on robot's erroneous behavior is crucial to enhance a robot intelligence for a 'flawless' human-robot interaction. Motivating humans to engage more actively for this purpose is however difficult. To alleviate such strain, this research proposes a novel approach, a growth and regression metaphoric interaction design inspired from human's communicative, intellectual, social competence aspect of developmental stages. We implemented the interaction design principle unto a conversational agent combined with a set of synthetic sensors. Within this context, we aim to show that the agent successfully encourages the online labeling activity in response to the faulty behavior of robots as a supervision process. The field study is going to be conducted to evaluate the efficacy of our proposal by measuring the annotation performance of real-time activity events in the wild. We expect to provide a more effective and practical means to supervise robot by real-time data labeling process for long-term usage in the human-robot interaction.
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UR - http://www.scopus.com/inward/citedby.url?scp=85063983913&partnerID=8YFLogxK
U2 - 10.1109/HRI.2019.8673212
DO - 10.1109/HRI.2019.8673212
M3 - Conference contribution
AN - SCOPUS:85063983913
T3 - ACM/IEEE International Conference on Human-Robot Interaction
SP - 646
EP - 647
BT - HRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction
PB - IEEE Computer Society
ER -