Industrial Microcontroller Based Neural Network Controlled Autonomous Vehicle
Journal Title: International Journal of Modern Engineering Research (IJMER) - Year 2014, Vol 4, Issue 5
Abstract
Navigation comprises two tasks hurdle avoidance and goal reaching. Hurdle avoidance is achieved with the help of ultrasonic sensors and IR sensors. The data from these sensors is given to neural network running inside the primary microcontroller. To minimize the computational burden on the microcontroller, a neural network is implemented with piecewise linear approximation of tangent-sigmoid activation function for neurons. Goal reaching behavior involves the data from the ultrasonic sensors, IR sensors and GPS receiver which is processed by another microcontroller. The goal is a set of latitude and longitude location to which the robot need to navigate. The primary microcontroller fetches the desired data and generates motion commands for robot. A GSM modem which is interfaced to the main controller is used for selecting start and goal stations for robot inside the university campus
Authors and Affiliations
D. Praveen Kumar1 , G. Sai Sudarsan2 , P. Dinesh3 , K Anil4 , Y. Govardhan5
Keywords
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