IROS 2019poster6 citations

Can User-Centered Reinforcement Learning Allow a Robot to Attract Passersby without Causing Discomfort?

Yasunori Ozaki, Tatsuya Ishihara, Narimune Matsumura, Tadashi Nunobiki

Abstract

The aim of our study is to develop a method by which a social robot can greet passersby and get their attention without causing them to suffer discomfort. Social robots now function in a number of customer service roles, such as receptionists, guides, and exhibitors. However, sudden greetings from a robot can startle passersby. Therefore, we developed a method that allows social robots to adapt their mannerisms situationally based the results of related work. Our proposed method, user-centered reinforcement learning, enables robots to greet passersby without causing them discomfort (p<0.01). Our field experiment in an office entrance demonstrated that our method meets this requirement.

BibTeX
@inproceedings{iros2019_canusercenteredr,
  title = {Can User-Centered Reinforcement Learning Allow a Robot to Attract Passersby without Causing Discomfort?},
  author = {Yasunori Ozaki and Tatsuya Ishihara and Narimune Matsumura and Tadashi Nunobiki},
  booktitle = {IROS 2019},
  year = {2019}
}