Neural network control of a wheeled mobile robot based on optimal trajectories. (21st April 2020)

• Record Type: Journal Article
• Authors: Bozek, Pavol; Karavaev, Yury L; Ardentov, Andrey A; Yefremov, Kirill S
• Is Part Of: International journal of advanced robotic systems. Volume 17:Number 2(2020:Mar./Apr.)
• Publication Date: 2020-04-21
• Subjects: Wheeled mobile robots -- robust -- adaptive and optimal control -- collision avoidance and multi-vehicle systems -- path planning and navigation -- robot learning; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881420916077
• Languages: English
• ISSNs: 1729-8806

Abstract

This article is concerned with developing an intelligent system for the control of a wheeled robot. An algorithm for training an artificial neural network for path planning is proposed. The trajectory ensures steering optimal motion from the current position of the mobile robot to a prescribed position taking its orientation into account. The proposed control system consists of two artificial neural networks. One of them serves to specify the position and the size of the obstacle, and the other forms a continuous trajectory to reach it, taking into account the information received, the coordinates, and the orientation at the point of destination. The neural network is trained on the basis of samples obtained by modeling the equations of motion of the wheeled robot which ensure its motion along trajectories in the form of Euler's elastica.