Improving a Wall-Following Robot Performance with a PID-Genetic Algorithm Controller

Abstract

A wall-following robot needs a robust controller that navigate robot based on the specified distance from the wall. The usage of PID controller has been successfully minimizing the dynamic error of wall-following robot. However, a manual setting of three unknown parameters of PID-controller often precisely increase instability. Hence, recently there are many approaches to solve this issue. This paper presents an approach to obtaining those PID parameters automatically by utilizing the role of Genetic Algorithm. The proposed method was simulated using MATLAB and tested in a real robot. Based on several experiments results it has been showing the effectiveness of reducing the dynamic error of the wall-following robot.