COMPARING DIFFERENT NAVIGATION TECHNOLOGIES FOR AUTOMATED GUIDED VEHICLES: AN APPLICATION STUDY

Automated Guided Vehicles have gained prominence as flexible and adaptable assets in a variety of industries in the ever-changing automation landscape. To navigate complex environments autonomously, AGVs rely on precise navigation technologies. This study examines and compares various navigation technologies in the context of AGVs, focusing espcially on Autonomous Mobile Robots (AMRs) their real-world applications and performance. The research looks at a variety of navigation technologies such as LiDAR-based systems, vision-based systems, simultaneous localization and mapping (SLAM), magnetic guiding, and hybrid approaches. It investigates the basic concepts, benefits, and drawbacks of each technology, emphasising its applicability for various tasks and operational scenarios in the context of AMRs. The paper includes a series of application-driven case studies to evaluate the real-world performance of different navigation systems. These examples illustrate how AMRs equipped with various navigation systems perform well in a variety of contexts, including busy warehouses, sophisticated layouts, and changing surroundings. Furthermore, the paper tackles crucial variables impacting the selection of navigation technology for AMRs, such as economic considerations, compatibility to existing infrastructures, and simplicity of maintenance. It also examines developing trends and future prospects in AMR navigation, such as the integration of AI and collaborative robotic systems. Finally, this study provides significant information to decision-makers seeking to maximise the benefits of AMRs in their operations through intelligent navigation technology selection. It is a must-have resource for companies looking to optimise their automation initiatives in a fast changing industrial context.