<![CDATA[Warehouses are increasingly adopting automation technologies to improve operational efficiency, inventory accuracy, and process flexibility in response to the growing demands of modern logistics and supply chain systems. Among these technologies, Autonomous Mobile Robots (AMRs) have emerged as a key enabler of smart warehouse operations by providing autonomous transportation, intelligent navigation, and real-time decision-making capabilities. This study aims to develop a Smart Warehouse Framework using Autonomous Mobile Robots that integrates warehouse management, robot navigation, Internet of Things (IoT) devices, and real-time communication systems into a unified architecture. The proposed framework incorporates AMRs, RFID readers, barcode scanners, IoT sensors, Warehouse Management Systems (WMS), fleet management systems, and cloud-based databases to support intelligent warehouse operations. A simulation-based evaluation was conducted using realistic warehouse scenarios to assess the framework's performance based on operational and navigation metrics. The results indicate that the proposed framework significantly improves warehouse efficiency by reducing task completion time from 15 minutes to 7 minutes and decreasing average travel distance from 120 m to 65 m. Furthermore, warehouse throughput increased from 80 to 150 orders per day, while order-picking accuracy improved from 92% to 98%. Navigation performance also demonstrated high effectiveness, achieving mapping accuracy of 97.5%, localization accuracy of 98.7%, and obstacle avoidance success rates exceeding 98%. These findings demonstrate that the proposed Smart Warehouse Framework provides a scalable, intelligent, and efficient solution for Warehouse 4.0 implementation and supports the adoption of autonomous logistics systems in modern industrial environments.]]>
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