Following drive control of small mobile robots using machine learning with FOMO

Abstract

In this paper, we propose a method for controlling following vehicles based on image processing and machine learning using an object detection algorithm (FOMO). In this study, we develop a cooperative work algorithm that combines image processing and communication using a small robot equipped with a microcomputer and a small camera that can communicate wirelessly. First, we describe a method for estimating the distance to the leading vehicle and the attitude angle of the following vehicle by machine learning of logo images using Edge Impulse. Next, we explain a simple PID control law that can maintain the distance and attitude angle between the vehicles. The proposed method is characterized by sharing motor speed commands via wireless communication, and we propose a control algorithm that enables stable following by combining the sharing method with the control law for distance and attitude. Finally, we evaluate the tracking accuracy by acquiring the trajectory of an actual driving experiment.