Experimental varification of autonomous movement based on selective tracking point in Pure Pursuit Algorithm and Dynamic Window Approach

Abstract

The method that combines Pure Pursuit Algorithm and Dynamic Window Approach (DWA) is effective for realizing stable running of the robot. However, DWA has the problem that it is caught by the local minima when surrounded by obstacles. In this study, we examine the solution of the problem by effectively selecting the tracking point of Pure Pursuit Algorithm. The experimental results in the real environment showed that the proposed method works effectively.