基于多模态融合感知的智能仓储盘库系统研究OA

To address the challenges of achieving reliable,efficient,and cost-effective storage location recognition and item identification in smart warehousing development,a phased intelligent inventory management system based on multimodal fusion perception was researched and proposed.Through analysis of limitations inherent to existing technologies such as RFID and pick-and-place imaging,a three-stage progressive solution was designed.In the first stage,visual recognition is employed for qualitative judgment regarding the presence or absence of storage locations and inventory changes.In the second stage,visual counting is combined with dynamic weighing technologies to achieve quantitative identification of goods quantity.The third stage addresses the core challenge of dynamic SKU binding by establishing a closed-loop process centered on anomaly detection and intelligent verification.Research demonstrates that this system significantly improves the real-time performance,accuracy,and cost-effectiveness of inventory management while maintaining operational continuity,providing an effective pathway toward realizing highly reliable digital twin warehouses and precise inventory management.