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Neural Computing and Applications

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01.11.2015 | Original Article

Spiking neural network-based target tracking control for autonomous mobile robots

verfasst von: Zhiqiang Cao, Long Cheng, Chao Zhou, Nong Gu, Xu Wang, Min Tan

Erschienen in: Neural Computing and Applications | Ausgabe 8/2015

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Abstract

In this paper, a target tracking controller based on spiking neural network is proposed for autonomous robots. This controller encodes the preprocessed environmental and target information provided by CCD cameras, encoders and ultrasonic sensors into spike trains, which are integrated by a three-layer spiking neural network (SNN). The outputs of SNN are generated based on the competition between the forward/backward neuron pair corresponding to each motor, with the weights evolved by the Hebbian learning. The application to target tracking of a mobile robot in unknown environment verifies the validity of the proposed controller.

Vorheriger Artikel Predictive clustering on non-successive observations for multi-step ahead chaotic time series prediction

Nächster Artikel Adaptive neural control with intercepted adaptation for time-delay saturated nonlinear systems

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Titel: Spiking neural network-based target tracking control for autonomous mobile robots
verfasst von: Zhiqiang Cao
Long Cheng
Chao Zhou
Nong Gu
Xu Wang
Min Tan
Publikationsdatum: 01.11.2015
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 8/2015
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-015-1848-5

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