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
Link To Document :
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