Gait measurement for human behavior estimation against autonomous mobile robot

Ayanori Yorozu, Masaki Takahashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To realize a safe collision avoidance of autonomous mobile robots, understanding human behavior against the robots is important. This paper has proposed a gait measurement method for human behavior estimation against autonomous mobile robot. The proposed method using a laser range sensor consists of five observed leg patterns recognition and global nearest neighbor (GNN)-based data association with a variable validation region based on the state of each leg. To verify the effectiveness of the proposed system, a verification test in a hospital that staff is recruited as participants were carried out. From the experimental results in the hospital, we confirm that the proposed method can reduce the chance of losing track of both legs and the variable validation region can reduce the chance of false tracking.

Original languageEnglish
Title of host publicationAdvances in Intelligent Systems and Computing
PublisherSpringer Verlag
Pages1021-1033
Number of pages13
Volume302
ISBN (Print)9783319083377
DOIs
Publication statusPublished - 2016
Event13th International Conference on Intelligent Autonomous Systems, IAS 2014 - Padova, Italy
Duration: 2014 Jul 152014 Jul 18

Publication series

NameAdvances in Intelligent Systems and Computing
Volume302
ISSN (Print)21945357

Other

Other13th International Conference on Intelligent Autonomous Systems, IAS 2014
CountryItaly
CityPadova
Period14/7/1514/7/18

Keywords

  • Autonomous mobile robot
  • Data association
  • Global nearest neighbor
  • Kalman filter
  • Laser range sensor
  • Leg tracking

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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  • Cite this

    Yorozu, A., & Takahashi, M. (2016). Gait measurement for human behavior estimation against autonomous mobile robot. In Advances in Intelligent Systems and Computing (Vol. 302, pp. 1021-1033). (Advances in Intelligent Systems and Computing; Vol. 302). Springer Verlag. https://doi.org/10.1007/978-3-319-08338-4_74