Human tracking of a mobile robot with an onboard LRF (Laser Range Finder) using human walking motion analysis

Yoonchang Sung, Woojin Chung

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

9 Citations (Scopus)

Abstract

Nowadays, human-following is becoming one of the key issues of a human-robot interaction. An LRF (Laser Range Finder) might be the appropriate sensor in dealing with a human-following since it gives accurate information on a distance. Both extracting leg images from an LRF and interpreting those images over a time period as a same person are important. In this paper, we propose how to group legs into a person from laser scanned images and how to track a target person robustly over a time period using attributes we defined. The proposed methods were successfully verified through an experiment.

Original languageEnglish
Title of host publicationURAI 2011 - 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence
Pages366-370
Number of pages5
DOIs
Publication statusPublished - 2011
Event2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2011 - Incheon, Korea, Republic of
Duration: 2011 Nov 232011 Nov 26

Publication series

NameURAI 2011 - 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence

Other

Other2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2011
CountryKorea, Republic of
CityIncheon
Period11/11/2311/11/26

Keywords

  • Human-following
  • Human-robot interaction
  • LRF
  • Tracking method

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications

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  • Cite this

    Sung, Y., & Chung, W. (2011). Human tracking of a mobile robot with an onboard LRF (Laser Range Finder) using human walking motion analysis. In URAI 2011 - 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence (pp. 366-370). [6145998] (URAI 2011 - 2011 8th International Conference on Ubiquitous Robots and Ambient Intelligence). https://doi.org/10.1109/URAI.2011.6145998