Application of Convolution Neural Network in Design and Fabrication of Robots for Transporting Goods in Factories

Abstract

Nowadays, the use of freight robots in factories will help people reduce their labor force and move into difficult and dangerous places more easily. Only smart robots will help people move equipment, goods to destinations that have been designed to own lanes in factories or remotely control these cargo robots to move following the demands of the controller. Goods will be delivered to the right place, helping to reduce labor costs for factories, increase productivity, thereby increasing the profits of businesses. Understanding the necessity of the design of transport robot and the development of artificial intelligence field along with the development of some types of embedded computers, the research team proposed a method to use convolutional neural networks deployed on the embedded computer platform to design a smart robot model to transport goods in the factory.