Autonomous Mobile Robots for Smart Warehouse Logistics Optimization

This study investigates the optimization of smart warehouse logistics using autonomous mobile robots (AMRs) and proposes an integrated framework for improving order fulfillment, routing efficiency, and warehouse throughput. The proposed framework combines sensor-based autonomous navigation, a warehouse management system, fleet coordination, reinforcement-learning-based task allocation, dynamic path planning, and energy-aware scheduling. A simulated warehouse comprising 1,000 storage locations and 50 AMRs is used for performance evaluation. Compared with manual warehouse operations, the proposed AMR system reduces average order fulfillment time from 18.4 to 11.2 min (39.1% reduction) and increases throughput from 320 to 470 orders/hour (a 46.9% increase). Furthermore, worker travel distance decreases by 67.3%, while operational cost decreases by 34.4%. The results demonstrate that coordinated AMR deployment can significantly improve warehouse productivity, operational flexibility, and resource utilization, supporting the development of intelligent Industry 4.0 logistics systems.