Robotic Order Allocation Using Logical Warehouse Partitions
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Solution Overview
Problem
Traditional physical partitioning in robotic warehouse systems is inflexible and inefficient, limiting robot utilization and order processing efficiency due to fixed storage locations, which hinders the full utilization of the robotic inventory system's flexibility and compliance.
Innovation Solution
Implementing a logical partitioning method that dynamically assigns orders to operating positions based on SKU clusters and historical order data, allowing robots to transfer inventory containers between logical partitions to optimize resource allocation and reduce transfer distances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If physical partitioning is used to store items in fixed locations, then item storage is simple and manageable, but robot transfer distances increase and order processing efficiency decreases
Solution Approach 1:
The system transitions from static physical partitioning to dynamic logical partitioning, where item locations are not fixed but can be dynamically reassigned based on order requirements. The control server dynamically determines optimal storage locations and retrieves items from various partitions based on real-time order needs, enabling flexible adaptation to different order scenarios and reducing robot transfer distances.
2Device complexity
If physical partitioning is used with fixed item locations, then partition management is straightforward, but robot utilization rate is low
Solution Approach 1:
The control server performs multiple functions: it manages logical partitions, determines optimal item locations, assigns retrieval tasks to robots, and coordinates operating positions. This centralized intelligent control enables the system to handle diverse order scenarios efficiently, maximizing robot utilization by dynamically assigning tasks based on current system state and order requirements.
3Ease of manufacture
If items are stored in fixed physical partitions, then storage organization is simple, but average transfer distance for robots increases
Solution Approach 1:
The system introduces a logical partitioning dimension that operates independently from physical storage locations. Instead of being constrained by fixed physical partitions, items are organized into logical partitions that can span multiple physical locations. This allows the system to optimize transfer distances by selecting the closest available item location for each order while maintaining logical organization.
Data Source
AI summary
Disclosed are an order processing method, apparatus and device, and a storage medium. The method comprises: determining a logical partition to which a target order belongs from a plurality of logical partitions as a target logical partition, wherein one logical partition is associated with at least one station and a plurality of inventory containers, and at least one inventory container of a plurality of inventory containers associated with the target logical partition accommodates inventory items required by the target order; allocating the target order to a station associated with the target logical partition, and taking the station as a target station; and controlling a robot to carry a target inventory container, accommodating the inventory items required by the target order, of the plurality of inventory containers associated with the target logical partition to the target station.