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Title:
mobile robots' wall-following controller based on probabilistic spiking neuron model
Author: Wang Xiuqing ; Hou Zeng-Guang ; Tan Min ; Wang Yongji ; Xie Fei
Source: Advanced Materials Research
Conference Name: 2012 International Conference on Advances in Mechanics Engineering, ICAME 2012
Conference Date: August 3, 2012 - August 5, 2012
Issued Date: 2012
Conference Place: Hong kong
Keyword: Behavioral research ; Mobile robots ; Neural networks ; Neurons
Indexed Type: EI
ISSN: 1022-6680
ISBN: 9783037855287
Department: (1) Hebei Normal University Shijiazhuang 050031 China; (2) State Key Laboratory of Complex Systems and Intelligence Science Institute of Automation The Chinese Academy of Sciences Beijing 100090 China; (3) Laboratory for Internet Technologies Institute of Software The Chinese Academy of Sciences South Fourth Street Zhong Guan Cun Beijing 100190 China; (4) State Key Laboratory of Computer Science Institute of Software The Chinese Academy of Sciences Beijing 100190 China
Abstract: This paper focuses on the third generation of neural networks- Spiking neural networks (SNNs), the novel Spiking neuron model- probabilistic Spiking neuron model (pSNM), and their applications. pSNM is used in mobile robots' behavior control, and a novel mobile robots' wall-following controller based on pSNM is proposed. In the pSNM controller, Spiking time-delayed coding is used for the sensory neurons of the input layer and pSNM is used for the motor neurons in the output layer. Thorpe and Hebbian learning rules are used in the controller. The experimental results show that the controller can control the mobile robots to follow the wall clockwise and counterclockwise successfully. The structure of the controller is simple, and the controller can study online. © (2012) Trans Tech Publications, Switzerland.
English Abstract: This paper focuses on the third generation of neural networks- Spiking neural networks (SNNs), the novel Spiking neuron model- probabilistic Spiking neuron model (pSNM), and their applications. pSNM is used in mobile robots' behavior control, and a novel mobile robots' wall-following controller based on pSNM is proposed. In the pSNM controller, Spiking time-delayed coding is used for the sensory neurons of the input layer and pSNM is used for the motor neurons in the output layer. Thorpe and Hebbian learning rules are used in the controller. The experimental results show that the controller can control the mobile robots to follow the wall clockwise and counterclockwise successfully. The structure of the controller is simple, and the controller can study online. © (2012) Trans Tech Publications, Switzerland.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15837
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Wang Xiuqing,Hou Zeng-Guang,Tan Min,et al. mobile robots' wall-following controller based on probabilistic spiking neuron model[C]. 见:2012 International Conference on Advances in Mechanics Engineering, ICAME 2012. Hong kong. August 3, 2012 - August 5, 2012.
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