Verbal guidance for sit-to-stand support system

被引:0
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作者
Mizuki Takeda
Yasuhisa Hirata
Yueh-Hsuan Weng
Takahiro Katayama
Yasuhide Mizuta
Atsushi Koujina
机构
[1] Tohoku University,Department of Robotics
[2] Tohoku University,The Frontier Research Institute for Interdisciplinary Sciences
[3] RT.WORKS Co.,undefined
[4] Ltd.,undefined
来源
关键词
Care robot; Sit-to-stand support; Physically assistive system; Human–robot interaction; Verbal guidance; Accountability;
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摘要
Artificial intelligence (AI)-based robots have become popular in various fields, thereby increasing the demand for care robots. Such care robots recognize or estimate factors such as human states and then perform actions depending on the estimation results. If the humans cooperating with robots do not understand robot functions well, the task will not be performed appropriately. Additionally, it is possible that the estimation may be incorrect. Robots may make mistakes, and there is a risk that these mistakes may not be understood by humans. In such cases, robots are not useful, and this may hinder the cooperation between humans and robots. There are several ways to deal with this issue including improving estimation and information representation. We can know what is important to design care robots by analyzing the influence of factors including accurate estimation and contents and timing of information representation. We developed a robot for analysis that can support a human during standing, by raising its armrest. The developed robot raises its armrest when the user leans on it. In the nursing-care field, verbal communication is important. Hence, we also adopt a verbal guidance for information representation. Verbal guidance to encourage a user to stand up and countdown timer representations are adopted. Initially, an experiment is conducted to validate the usability of the system that acts according to considerably accurate estimations. The experimental results show that system without verbal guidance causes anxiety to humans and the system becomes not useful, even if the human state is detected accurately. Furthermore, we determine the appropriate content and timing of verbal guidance based on the results. Subsequently, we conduct an experiment to confirm that the proposed method is applicable under imperfect estimations.
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