mobile robots' wall-following controller based on probabilistic spiking neuron model

ISCAS OpenIR

	mobile robots' wall-following controller based on probabilistic spiking neuron model
	Wang Xiuqing; Hou Zeng-Guang; Tan Min; Wang Yongji; Xie Fei
	2012
会议名称	2012 International Conference on Advances in Mechanics Engineering, ICAME 2012
会议录名称	Advanced Materials Research
页码	1547-1551
会议日期	August 3, 2012 - August 5, 2012
会议地点	Hong kong
收录类别	EI
ISSN	1022-6680
ISBN	9783037855287
部门归属	(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
摘要	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.; 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.
关键词	Behavioral Research Mobile Robots Neural Networks Neurons
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/15837
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Wang Xiuqing,Hou Zeng-Guang,Tan Min,et al. mobile robots' wall-following controller based on probabilistic spiking neuron model[C],2012:1547-1551.