a target-reaching controller for mobile robots using spiking neural networks

ISCAS OpenIR

	a target-reaching controller for mobile robots using spiking neural networks
	Wang Xiuqing; Hou Zeng-Guang; Lv Feng; Tan Min; Wang Yongji
	2012
会议名称	19th International Conference on Neural Information Processing, ICONIP 2012
会议录名称	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
页码	652-659
会议日期	November 12, 2012 - November 15, 2012
会议地点	Doha, Qatar
收录类别	EI
ISSN	0302-9743
ISBN	9783642344770
部门归属	(1) Vocational and Technical Institute Hebei Normal University Shijiazhuang Hebei 050031 China; (2) State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100090 China; (3) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100190 China
摘要	Autonomous navigation plays important role in mobile robots. In this paper, a navigation controller based on spiking neural networks (SNNs) for mobile robots is presented. The proposed target-reaching navigation controller, in which the reactive architecture is used, is composed of three sub-controllers: the obstacle-avoidance controller and the wall-following controller using spiking neural networks (SNNs), and the goal-reaching controller. The experimental results show that the navigation controller can control the mobile robot to reach the target successfully while avoiding the obstacle and following the wall to get rid of the deadlock caused by local minimum. The proposed navigation controller does not require accurate mathematical models of the environment, and is suitable to unknown and unstructured environment. © 2012 Springer-Verlag.; Autonomous navigation plays important role in mobile robots. In this paper, a navigation controller based on spiking neural networks (SNNs) for mobile robots is presented. The proposed target-reaching navigation controller, in which the reactive architecture is used, is composed of three sub-controllers: the obstacle-avoidance controller and the wall-following controller using spiking neural networks (SNNs), and the goal-reaching controller. The experimental results show that the navigation controller can control the mobile robot to reach the target successfully while avoiding the obstacle and following the wall to get rid of the deadlock caused by local minimum. The proposed navigation controller does not require accurate mathematical models of the environment, and is suitable to unknown and unstructured environment. © 2012 Springer-Verlag.
关键词	Collision Avoidance Data Processing Human Computer Interaction Mathematical Models Navigation Neural Networks
主办者	United Development Company PSC (UDC); Qatar Petrochemical Company; ExxonMobil; Qatar Petroleum; Texas A and M University at Qatar; Asia Pacific Neural Network Assembly
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/15840
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,Lv Feng,et al. a target-reaching controller for mobile robots using spiking neural networks[C],2012:652-659.