A target-reaching controller for mobile robots using spiking neural networks
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
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The ability of cognition and recognition for complex environment is very important for a real autonomous robot. A Corridor-Scene-Classifier based on spiking neural networks (SNN) for mobile robot is designed to help the mobile robot to locate correctly. In the SNN classifier, the integrate-and-fire model (IAF) spiking neuron model is used and there is lateral inhibiting in the output layer. The Winner-Take-All rule is used to modify the connecting weights between the hidden layer and the outputting layer. The experimental results show that the Corridor-Scene-Classifier is effective and it also has strong robustness.