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This paper describes the implementation of a neural network based hurdle avoidance controller for a car like robot using a low cost single chip 89C52 microcontroller. The neural network is the multilayer feed-forward network with back propagation training algorithm. The network is trained offline with tangent-sigmoid as activation function for neurons and is implemented in real time with piecewise...
In this paper, design of a low cost autonomous vehicle based on neural network for navigation in unknown environments is presented. The vehicle is equipped with four ultrasonic sensors for hurdle distance measurement, a wheel encoder for measuring distance traveled, a compass for heading information, a GPS receiver for goal position information, a GSM modem for changing destination place on run time...
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