• DocumentCode
    3480058
  • Title

    Detecting abnormal state of elderly for service robot with H-FCM

  • Author

    Li, Haitao ; Kong, Lingfu ; Wu, Peiliang

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao, China
  • fYear
    2009
  • fDate
    5-7 Aug. 2009
  • Firstpage
    1867
  • Lastpage
    1870
  • Abstract
    Detecting abnormal state of elder from sensor is very important for high-level activity inference of service robot. This paper proposes a model to solve this problem using location information. Firstly, the feature can be extracted from location information using the SLAM Map, and the vector based on l,thetas is calculated. Then approach of clustering the feature vector based on H-FCM algorithm. Experiment results demonstrate that the model is feasible to learn human state habit and can afford a judging gist to detect persons´ abnormal state.
  • Keywords
    SLAM (robots); feature extraction; handicapped aids; inference mechanisms; mobile robots; pattern clustering; robot vision; service robots; H-FCM algorithm; SLAM Map; elder abnormal state detection; high-level activity inference; location information extraction; service robot; Cameras; Clustering algorithms; Data mining; Feature extraction; Global Positioning System; Humans; Logistics; Robotics and automation; Senior citizens; Service robots; Abnormal State; H-FCM Algorithm; Mobile Service Robot;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4244-4794-7
  • Electronic_ISBN
    978-1-4244-4795-4
  • Type

    conf

  • DOI
    10.1109/ICAL.2009.5262649
  • Filename
    5262649