DocumentCode :
1930238
Title :
A sensory network for perception-based robotics using neural networks
Author :
Kubota, Naoyuki ; Hashimoto, Setsuo ; Kojima, Fumio
Author_Institution :
Dept. of Human & Artificial Intelligent Syst., Fukui Univ., Japan
Volume :
4
fYear :
2003
fDate :
20-24 July 2003
Firstpage :
3151
Abstract :
This paper discusses fault tolerance in perception-based robotics from the viewpoint of ecological psychology. A prediction-based sensory network using neural networks is proposed for detecting a fault in sensing systems. Furthermore, a transformation matrix is applied for extracting perceptual information from the sensory inputs that might include fault inputs owing to breakdown. We apply the proposed method to a mobile robot. Computer simulations show the proposed method can detect the fault of sensors and can extract perceptual information used for decision making.
Keywords :
fault diagnosis; fault tolerance; intelligent robots; mobile robots; neural nets; sensors; ecological psychology; fault detection; mobile robot; neural networks; perception-based robotics; perceptual information extraction; prediction-based sensory network; sensory network; transformation matrix; Computer simulation; Data mining; Decision making; Electric breakdown; Fault detection; Fault tolerance; Mobile robots; Neural networks; Psychology; Robot sensing systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN :
1098-7576
Print_ISBN :
0-7803-7898-9
Type :
conf
DOI :
10.1109/IJCNN.2003.1224076
Filename :
1224076
Link To Document :
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