A Systematic Literature Review of Autonomous Line-Following Robots using Reinforcement Learning

Abstract

Mobile robots have gained importance due to its capability to perform autonomous tasks. Line-following robots are mobile robots which have become a growing topic of research, as they serve as a platform for understanding complex concepts, such as control, which makes them suitable for the application of Artificial Intelligence (AI). There are competitions around the world focused on this kind of robots. Accurate mathematical modeling of line-following robots and the environment in which they will be used can be difficult. Reinforcement learning is an AI technique that deals precisely with creating model-free algorithms, which are suitable for this application. This review article aimed to look for articles on line-following robots using reinforcement learning in order to analyze the state of the art of this branch of artificial intelligence in robotics.