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Tatsuya Ishihara

3 accepted papers

2019

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

IROS 2019poster

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…

Cited by 6SourceScholar
2018

Machine Learning Based Skill-Level Classification for Personal Mobility Devices Using Only Operational Characteristics

IROS 2018poster

Some electric-powered wheelchairs are recently redefined as personal mobility devices. Their users are not only elderly or handicapped people, but also passengers with large baggage or pedestrians going from station to destination, i.e., last-mile transport. Consequently, people with different opera…

Cited by 1SourceScholar
2017

Inference Machines for supervised Bluetooth localization

ICASSP 2017accepted

State space models, such as Kalman filters or Particle filters, have been applied to improve the accuracy of radio-wave-based localization. However, these models can drift radically when assumptions of the models are violated, and they do not have a mechanism to fix errors. Therefore, we propose an…

Cited by 0SourceScholar