In recent years, all attention has been directed to the mobile robots (MRs) which are becoming increasingly popular across different sectors. They are used to assist work processes and accomplish tasks that are impossible or dangerous for human workers such as earthquakes, floods, active volcanos, or nuclear disasters. MRs have many applications in different fields such as commercial, recreational, agricultural sectors, hospital, policing, welding, surveillance, product deliveries, and aerial photography. The MR encounters difficult circumstances in its complex environment which may have a high density of obstacles, either static or dynamic or both, erratic sensor data, numerous robots doing distinct duties, and unpredictability conditions. These challenging conditions limit its capacity to choose the most appropriate path. Technology for MRs has advanced more lately, and a variety of autonomous navigation algorithms have made it possible for these MRs to navigate in dynamic and complex environments. This study aims to present a thorough and current review of the autonomous mobility of MRs which enable safe and effective navigation with a single or multi-robot. Furthermore, it provides a review for various automatic AI techniques for getting the optimal path planning for the MRs. A systematic analysis demonstrates the contributions and limitations of each technique to show the effectiveness of the presented work. Accordingly, this paper offers valuable guidance and reference for further investigations to enhance the autonomy of MRs.