Open AccessDEVELOPMENT AND MODELING OF AN ARTIFICIAL NEURAL NETWORK FOR THE AI-DRIVER IN THE COMPOSITION OF AN UNMANNED VEHICLE
Author(s) -
Alexander Vlasov,
Т. Круглова
Publication year - 2020
Publication title -
vestnik bgtu im. v.g. šuhova
Language(s) - English
Resource type - Journals
ISSN - 2071-7318
DOI - 10.34031/2071-7318-2020-5-8-101-110
Subject(s) - artificial neural network , artificial intelligence , computer science , robotics , task (project management) , advanced driver assistance systems , control engineering , engineering , robot , systems engineering
Improving control systems for unmanned vehicles is the most urgent task in robotics. The use of such a tool as artificial neural networks can solve problems with intelligent and adaptive control. The existing concept of AI driver (driver with artificial intelligence) implies a system capable of controlling the speed and position of an unmanned vehicle in space. This article proposes a method for developing an artificial neural network for an AI-driver, taking into account the appearance of obstacles in the path of an unmanned vehicle, compiling an empirical database for training, and modeling the developed system to obtain both a control signal and a trajectory. The proposed system consists of two artificial neural networks that divide the task of driving an unmanned vehicle into two sub-tasks: processing data from rangefinders and generating a speed setting signal for the left and right drives. This approach reduces the retraining of the neural network and allows you to get a smaller training error. The use of artificial intelligence will make it possible to increase the functionality and reliability of control systems for unmanned vehicles.