UM
Human-Robot Interaction Learning Using Demonstration-Based Learning and Q-Learning in a Pervasive Sensing Environment
Yunsick Sung1; Seoungjae Cho2; Kyhyun Um3; Young-Sik Jeong3; Simon Fong4; Kyungeun Cho3
2013-12-01
Source PublicationInternational Journal of Distributed Sensor Networks
ISSN1550-1477
Volume2013
Abstract

Given that robots provide services in any locations after they move toward humans, the pervasive sensing environment can provide diverse kinds of services through the robots not depending on the locations of humans. For various services, robots need to learn accurate motor primitives such as walking and grabbing objects. However, learning motor primitives in a pervasive sensing environment are very time consuming. Several previous studies have considered robots learning motor primitives and interacting with humans in virtual environments. Given that a robot learns motor primitives based on observations, a disadvantage is that there is no way of defining motor primitives that cannot be observed by a robot. In this paper, we develop a novel interaction learning approach based on a virtual environment. The motor primitives are defined by manipulating a robot directly using demonstration-based learning. In addition, a robot can apply Q-learning to learn interactions with humans. In an experiment, using the proposed method, the motor primitives were generated intuitively and the amount of movement required by a virtual human in one of the experiments was reduced by about 25% after applying the generated motor primitives.

DOIhttps://doi.org/10.1155/2013/782043
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Telecommunications
WOS IDWOS:000328062100001
PublisherSAGE PUBLICATIONS INC, 2455 TELLER RD, THOUSAND OAKS, CA 91320 USA
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Citation statistics
Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorKyungeun Cho
Affiliation1.The Department of Game Mobile Contents, Keimyung University, Daegu 704-701, Republic of Korea
2.Department of Multimedia Engineering, Graduate School of Dongguk University, Seoul 100-715, Republic of Korea
3.Department of Multimedia Engineering, Dongguk University, Seoul 100-715, Republic of Korea
4.Department of Computer and Information Science, University of Macau, Macau 3000, China
Recommended Citation
GB/T 7714
Yunsick Sung,Seoungjae Cho,Kyhyun Um,et al. Human-Robot Interaction Learning Using Demonstration-Based Learning and Q-Learning in a Pervasive Sensing Environment[J]. International Journal of Distributed Sensor Networks,2013,2013.
APA Yunsick Sung,Seoungjae Cho,Kyhyun Um,Young-Sik Jeong,Simon Fong,&Kyungeun Cho.(2013).Human-Robot Interaction Learning Using Demonstration-Based Learning and Q-Learning in a Pervasive Sensing Environment.International Journal of Distributed Sensor Networks,2013.
MLA Yunsick Sung,et al."Human-Robot Interaction Learning Using Demonstration-Based Learning and Q-Learning in a Pervasive Sensing Environment".International Journal of Distributed Sensor Networks 2013(2013).
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