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

Yifan Huang, Taiga Mori, Udara E. Manawadu, Mitsuhiro Kamezaki, Tatsuya Ishihara, Masahiro Nakano, Kohjun Koshiji, Naoki Higo, Toshimitsu Tubaki, Shigeki Sugano

研究成果: Conference contribution

抄録

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 operation skills and expectations on personal mobility would become new users of this kind of devices. Safe and comfort travel in human co-existing environment such as sidewalks and airports is a social expectation for personal mobility. In order to realize this, understanding the operation skill of each user by a practical and simple method is essential. This paper thus introduced a skill level classification method by machine learning using only joystick data as input. In order to determine the number of skill level clusters, basic 26 features of joystick operation data are used for unsupervised clustering (single-linkage). We then made evaluation indexes by using speed, speed control, and direction control. For a five-level classification by using gradient boosting as supervised learning, we achieved a 67% accuracy (tolerance: 0) and a 98% accuracy (tolerance: 1). Further analysis of the feature importance of gradient boosting revealed key features to a good operation. Results also show that skill level differed among people with different driving experiences.

本文言語English
ホスト出版物のタイトル2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ5469-5476
ページ数8
ISBN(電子版)9781538680940
DOI
出版ステータスPublished - 2018 12 27
イベント2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018 - Madrid, Spain
継続期間: 2018 10 12018 10 5

出版物シリーズ

名前IEEE International Conference on Intelligent Robots and Systems
ISSN(印刷版)2153-0858
ISSN(電子版)2153-0866

Conference

Conference2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
CountrySpain
CityMadrid
Period18/10/118/10/5

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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