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공지사항
논문명 |
Reactive virtual agent learning for NUI-based HRI applications |
논문종류 |
SCI |
저자 |
Daxing Jin, Seoungjae Cho, Yunsick Sung, Kyungeun Cho, Kyhyun Um |
Impact Factor |
1.331 |
게재학술지명 |
MULTIMEDIA TOOLS AND APPLICATIONS |
게재일 |
2016.12 |
The natural user interface (NUI) has been investigated in a variety of fields in application software. This paper proposes an approach to generate virtual agents that can support users for NUI-based applications through human–robot interaction (HRI) learning in a virtual environment. Conventional human–robot interaction (HRI) learning is carried out by repeating processes that are time-consuming, complicated and dangerous because of certain features of robots. Therefore, a method is needed to train virtual agents that interact with virtual humans imitating human movements in a virtual environment. Then the result of this virtual agent can be applied to NUI-based interactive applications after the interaction learning is completed. The proposed method was applied to a model of a typical house in virtual environment with virtual human performing daily-life activities such as washing, eating, and watching TV. The results show that the virtual agent can predict a human’s intent, identify actions that are helpful to the human, and can provide services 16 % faster than a virtual agent trained using traditional Q-learning. |
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