A review of path following control strategies for autonomous robotic vehicles: theory, simulations, and experiments

TL;DR

This review comprehensively analyzes various path following control strategies for autonomous robotic vehicles, categorizing methods, comparing their advantages, and validating them through experiments and simulations in marine vehicles.

Contribution

The paper provides a unified framework for understanding path following methods and introduces open-source tools for testing these strategies in simulation environments.

Findings

Most methods can be categorized into two groups based on error system stabilization.

Experimental validation was performed on marine vehicles demonstrating practical applicability.

Open-source simulation tools facilitate testing and development of path following algorithms.

Abstract

This article presents an in-depth review of the topic of path following for autonomous robotic vehicles, with a specific focus on vehicle motion in two dimensional space (2D). From a control system standpoint, path following can be formulated as the problem of stabilizing a path following error system that describes the dynamics of position and possibly orientation errors of a vehicle with respect to a path, with the errors defined in an appropriate reference frame. In spite of the large variety of path following methods described in the literature we show that, in principle, most of them can be categorized in two groups: stabilization of the path following error system expressed either in the vehicle's body frame or in a frame attached to a "reference point" moving along the path, such as a Frenet-Serret (F-S) frame or a Parallel Transport (P-T) frame. With this observation, we provide a unified formulation that is simple but general enough to cover many methods available in the literature. We then discuss the advantages and disadvantages of each method, comparing them from the design and implementation standpoint. We further show experimental results of the path following methods obtained from field trials testing with under-actuated and fully-actuated autonomous marine vehicles. In addition, we introduce open-source Matlab and Gazebo/ROS simulation toolboxes that are helpful in testing path following methods prior to their integration in the combined guidance, navigation, and control systems of autonomous vehicles.