NDLI: A sensory network for perception-based robotics using neural networks

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Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium

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A sensory network for perception-based robotics using neural networks

Content Provider	IEEE Xplore Digital Library
Author	Kubota, N. Hashimoto, S. Kojima, F.
Copyright Year	2003
Description	Author affiliation: Dept. of Human & Artificial Intelligent Syst., Fukui Univ., Japan (Kubota, N.)
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.
Sponsorship	Int. Neural Network Soc. IEEE Neural Networks Soc
Starting Page	3151
Ending Page	3156
File Size	376610
Page Count	6
File Format	PDF
ISBN	0780378989
ISSN	10987576
DOI	10.1109/IJCNN.2003.1224076
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-07-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot sensing systems Neural networks Fault detection Data mining Fault tolerance Psychology Electric breakdown Mobile robots Computer simulation Decision making
Content Type	Text
Resource Type	Article

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