https://scholars.lib.ntu.edu.tw/handle/123456789/581084
標題: | Deep learning based social context perception on human-robot interaction | 作者: | Luo R.C Hsieh C.K. REN-CHYUAN LUO |
關鍵字: | Behavioral research; Deep learning; Man machine systems; Robotics; Good services; Human behaviors; Human-Friendly Robots; Learning models; Situational context; Social behavior; Social context; Social environment; Human robot interaction | 公開日期: | 2017 | 來源出版物: | 49th International Symposium on Robotics, ISR 2017 | 摘要: | The objective of this paper is to develop a social co-robot for provision of "just-good services" using situational context based perception for perceiving human's mentation. In the near future, more and more human-friendly robots will be involved in human livelihood. In order to act more friendly in Human Social Environments (HSEs), robots should possess the ability of social context perception. In this paper, we propose a deep learning model, which learn from previous observations of human-robot interaction, to enable our robot to perceive a human's needs. Therefore, the appropriate social behaviors with respect to human's mental state would be reacted by robot. The experimental results demonstrate that the proposed deep learning model can significantly improve the accuracy of predicting a person's mentation from human behaviors. ? 49th International Symposium on Robotics, ISR 2017. All rights reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084160457&partnerID=40&md5=1dff9c778137b2f71bc7cb7f8e14f99a https://scholars.lib.ntu.edu.tw/handle/123456789/581084 |
顯示於: | 電機工程學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。