New Automated Guided Vehicle System Using Real-Time Holonic Scheduling for Warehouse Picking

Hiroshi Yoshitake, Ryota Kamoshida, Y. Nagashima

IEEE Robotics and Automation Letters · 2019 · 78 citations · 29 references

Concepts

TL;DR

AGV picking systems move entire shelves to pickers, boosting warehouse productivity, but conventional setups only transport sorting shelves after sorting completes. The authors propose a new AGV‑based robotic system for order picking in logistics warehouses. The system continuously transports sorting shelves during sorting and employs a real‑time holonic scheduling method to manage complex transport tasks, and its productivity was compared to a conventional method. The new system improves picking productivity, especially in larger work areas and for high‑mix, low‑volume orders, where it outperforms the conventional approach.

Abstract

We propose a new robotic system using an automated guided vehicle (AGV) for order picking in logistics warehouses. In AGV picking systems, AGVs transport the entire shelves including the required items (inventory shelves) or shipping boxes (sorting shelves) to the pickers instead of the pickers moving to the shelves, which improves the productivity of the picking activity in warehouses. In conventional systems, the sorting shelves are fixed or are transported only after the completion of the sorting work of the shelves. Our new system transports the sorting shelf even if the sorting shelf is in the middle of sorting. This system improves the productivity of picking activity by transporting both the shelves to appropriate locations at the appropriate time. To handle complex transport tasks, the proposed system requires a real-time scheduling method. This study applies a real-time holonic scheduling method to resolve scheduling problems. We evaluated the productivity of the proposed system and that of the conventional method that transports sorting shelves only after finishing the sorting work. The results show that the larger the working area and the higher mixed and lower-volume the picking orders are, the more efficiently the proposed method solves scheduling problems.

References

29