Unmanned vehicle trajectory tracking by neural networks

Abstract EN

This paper, deals with a path planning and intelligent control of an autonomous vehicle which should m^^e safely in its road partially structured.

This road, involves a number of obstacles like donkey, traffic lights and other vehicles.

In this paper, the Neural Networks (NN)-based technique Artificial Neural Network (ANN) is described to solve the motion-planning problem in Unmanned Vehicle (UV) control.

This is accomplished by choosing the appropriate inputs / outputs and by carefully training the ANN.

The network is supplied 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.

The network has been trained with a set of strategic input-output.

The results show the effectiveness of the technique used, the UV drives around avoiding obstacles.