Presentation 2001/10/12
Robot Navigation based on Time Delay Neural Networks
Tetsuro KOMATSU, Qiangfu ZHAO,
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Abstract(in English) Multilayer perceptron (MLP) is known as a good tool for robot control.Using MLP alone, however, we cannot get complex and intelligent behavior because a MLP makes decision based only on the current inputs and ignores the history. To avoid this problem, memory based neural network(MBNN) can be used. There are many models for MBNN, say recurrent neural network(RNN) and time-delay neural network(TDNN). In this study, we try to adopt TDNN with each hidden and output node being a finite-duration impulse response(FIR) filter. In this paper, we study the evolutionary learning of TDNN and verify the efficiency of TDNN through simulation. In addition, we point out some problems in using TDNN and propose the solution.
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Keyword(in English) Time-Delay Neural Network / robot navigatio / evolutionary learning
Paper # NC2001-60
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Conference Information
Committee NC
Conference Date 2001/10/12(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Robot Navigation based on Time Delay Neural Networks
Sub Title (in English)
Keyword(1) Time-Delay Neural Network
Keyword(2) robot navigatio
Keyword(3) evolutionary learning
1st Author's Name Tetsuro KOMATSU
1st Author's Affiliation University of Aizu Graduate School of Computer Science and Engineering()
2nd Author's Name Qiangfu ZHAO
2nd Author's Affiliation University of Aizu Graduate School of Computer Science and Engineering
Date 2001/10/12
Paper # NC2001-60
Volume (vol) vol.101
Number (no) 365
Page pp.pp.-
#Pages 5
Date of Issue