N. Khlif, N. Khraief and S. Belghith, Reinforcement Learning for Mobile Robot Navigation: An overview IEEE Information Technologies & Smart Industrial Systems (ITSIS), Paris, France, 2022, pp. 1-7 DOI: 10.1109/ITSIS56166.2022.10118362.
For several years, research shows that interest in autonomous mobile robots is increasing and it has more and more grown. Autonomous mobile robots is an object of discussion but nowadays it’s an emerging topic due to the all progress related to field like autonomous driving and UAV (drones). Integrating intelligence into robotic systems requires solving various research problems, including one of the most important problems of mobile robotic systems: navigation. Find the answers to the following three questions: What is the localisation of the robot? Where are the robot going? How can it get there? presenting the solution of mobile robot navigation problem. These questions are answered by basic navigation parts which are localization, mapping and path planning. The paper present an overview of research on autonomous mobile robot navigation. First, a quick introduction to the various features of navigation. We also discuss machine learning and reinforcement learning in mobile robotics. Furthermore, we will discuss some path planning techniques. Some future directions are also suggested.