Automated guided vehicles (AGVs) have recently acquired a lot of interest in the academic research field and industry applications due to a variety of advantages, including increased mobility and improved safety. AGVs are designed to maneuver following a predetermined path; however, if the path is blocked, how can the AGV avoid or pass through it by selecting the new path with the safest behavior? This article discovered a number of recent advanced methods that are widely employed in AGV operation with the aim of avoiding dynamic obstacles and being able to function in a complex environment. The most recent techniques for obstacle avoidance utilized with AGV have been evaluated in scholarly research that has been published in the last five years. In doing so, this review responds to three related questions: are the fundamental approaches for avoiding obstacles in AGV robot systems still applicable? 2) which is the most recent sensor technology used by the AGV robot to sense its surroundings? and 3) does the artificial intelligence (AI) method improve the AGV robot’s ability to make decisions and function autonomously? As a result, various fundamental and recent advances in methods are covered. This study is done to make it easier for researchers or engineers to comprehend and conduct more research.