Enhancement of pure-pursuit path-tracking algorithm with multi-goal selection
Ernő Horváth, Csaba Hajdu, Peter J. Koros · 2019
In this paper, we present an enhancement to the popular pure-pursuit algorithm, widely used in robotics and automotive applications. The original algorithm is simple and straightforward as it depends only on the very basic attributes of the kinematic model of the target mechanical system. The algorithm is usually tuned by choosing a look-ahead distance of points from the reference trajectory. On the other hand, pure-pursuit suffers from considerable tuning weaknesses highly attributed to improper selection of look-ahead distance, resulting in poor tracking performance. Our method proposes the dynamic change of lookahead distance based on selecting multiple-goal points, thus aiming a curvature fitting more the reference trajectory. Our work was motivated by an ongoing robotics and autonomous vehicle research project at our university.