Unmanned vehicle trajectory tracking by neural networks

This paper, deals with a path planning and intelligent control of an autonomous vehicle which should move 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.