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

Authors:
Xiuqing Wang;Zeng-Guang Hou;Feng Lv;Min Tan;Yongji Wang
Affiliations:
Vocational & Technical Institute, Hebei Normal University, Shijiazhuang, Hebei, China;State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, The Chinese Academy of Sciences, Beijing, China;Vocational & Technical Institute, Hebei Normal University, Shijiazhuang, Hebei, China;State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, The Chinese Academy of Sciences, Beijing, China;State Key Laboratory of Computer Science, Institute of Software, The Chinese Academy of Sciences, Beijing, China
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
Year:
2012

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Abstract

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.