Sensor-fusion in spiking neural network that generates autonomous behavior in real mobile robot

Fady Alnajjar, Kazuyuki Murase

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

We here introduce a novel adaptive controller for autonomous mobile robot that binds N types of sensory information. For each sensory modality, sensory-motor connection is made by a three-layered spiking neural network (SNN). The synaptic weights in the model have the property of spike timing-dependent plasticity (STDP) and regulated by presynaptic modulation signal from the sensory neurons. Each synaptic weight is incrementally adapted depending upon the firing rate of the presynaptic modulation signal and that of the hidden-layer neuron(s). Information from different types of sensors are bound at the motor neurons. A real mobile robot Khepera with the SNN controller quickly adapted into an open environment and performed the desired task successfully. This approach could be applicable to a robot with inputs of various sensory modalities and various types of motor outputs.

Original languageEnglish
Title of host publication2008 International Joint Conference on Neural Networks, IJCNN 2008
Pages2200-2206
Number of pages7
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 International Joint Conference on Neural Networks, IJCNN 2008 - Hong Kong, China
Duration: Jun 1 2008Jun 8 2008

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Conference

Conference2008 International Joint Conference on Neural Networks, IJCNN 2008
Country/TerritoryChina
CityHong Kong
Period6/1/086/8/08

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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