AUTOMATIC GUIDED VEHICLES: UN-MANNED LOGISTICS

Abstract

AGVs are a huge step forward in logistics since they don't require a driver. They are very useful for automating the moving and handling of goods in many different sectors. As the need for industrial processes to be more efficient, accurate, and cost-effective develops, AGVs have become an important part of production, storage, and distribution systems. This study goes into great detail regarding AGV technology, including its history, how it works, what it's used for currently, what problems it has, and what the future holds for it. The first part of the post speaks about what AGVs are and what makes them work. These parts include sensors, navigation systems, and control systems that let them move about in organized settings without help. The paper provides an in-depth analysis of the technical components of automated guided vehicles (AGVs) and also provides an explanation of the primary benefits that these systems may provide to companies. Some of these benefits include reduced costs associated with labor, processes that are more efficient, increased levels of safety, and improved procedures for the management of commodities. Because they reduce the number of humans who need to be engaged, automated guided vehicles (AGVs) make things simpler and safer. This is due to the fact that they make it safer to carry out operations performed by hand that are either risky or repetitious. The article discusses some of the issues and gaps in the research that need to be filled in order for autonomous guided vehicles (AGVs) to be employed to their full potential, despite the fact that they have a lot of positive qualities. One of the most significant challenges is to make it simpler for automated guided vehicles (AGVs) to travel in environments that are not well- organized and are constantly changing. Other challenges include extending the lifespan of batteries and reducing their energy consumption. Lastly, it is essential to ensure that humans and AGVs can collaborate effectively, especially when both are present. It is still difficult to get a large number of automated guided vehicles (AGVs) and other automated systems to cooperate and perform effectively, which is one of the reasons why there are still research gaps in the field of fleet management. AGV integration with Industry 4.0, the IoT, and smart factories is discussed as a future trend. These technologies combined with AGVs are projected to provide highly efficient, networked logistics ecosystems with real-time data interchange, predictive analytics, and autonomous decision-making. The paper stresses the relevance of AI and machine learning in allowing AGVs to adapt to new jobs and situations without human intervention, expanding unmanned logistics.