Neural Network Navigation Technique for Unmanned Vehicle
Abstract
Using a neural network (ANN) for the brain, we want a vehicle to drive by itself avoiding obstacles. We accomplish this by choosing the appropriate inputs/outputs and by carefully training the ANN. We feed the network with distances of the closest obstacles around the vehicle to imitate what a human driver would see. The output is the acceleration and steering of the vehicle. We also need to train the network with a set of strategic input-output. The result is impressive, for a couple of neurons! The unmanned vehicle (UV) drives around avoiding obstacles, but some improvement or modification can be done to make this software work for a specific purpose.
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PDFDOI: https://doi.org/10.11591/eei.v3i3.291
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Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191
,
e-ISSN: 2302-9285
This journal is published by the
Institute of Advanced Engineering and Science (IAES)
.