Robot-Based Subarea Picking for Flexible Warehouse Zoning
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Solution Overview
Problem
Conventional static subarea picking methods in warehouse logistics cannot meet the requirements of small-batch high-frequency orders in terms of efficiency and flexibility, particularly in an electronic commerce environment, due to fixed conveyor belts and picker allocation, leading to space occupation and reduced efficiency.
Innovation Solution
A robot-based subarea logistics picking method that includes acquiring order and location information, calculating a planned path for robots, and implementing human-machine configuration to optimize warehouse space use and picker allocation, thereby enhancing flexibility and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conveyor belts are used for subarea picking, then picking efficiency is improved and travel waste is avoided, but warehouse space flexibility is reduced and space occupation increases
Solution Approach 1:
The patent replaces fixed conveyor belts with mobile robots that can dynamically adjust their positions and routes. The robots move on the ground surface without fixed installation, allowing the system to adapt to different picking scenarios and warehouse layouts. This dynamic approach maintains high picking efficiency while eliminating the space occupation and flexibility limitations of fixed conveyor systems.
Solution Approach 2:
The patent substitutes the mechanical conveyor belt system with an automated mobile robot system. Instead of using fixed mechanical transmission devices, the system employs intelligent robots equipped with sensors and navigation capabilities to transport goods. This substitution eliminates the need for fixed infrastructure while maintaining automated picking efficiency.
2Ease of manufacture
If fixed conveyor belts are installed, then picking area arrangement is determined, but manpower allocation flexibility is reduced and congestion occurs during high-load work
Solution Approach 1:
The mobile robot system allows dynamic reallocation of picking resources based on real-time workload demands. Robots can be reassigned to different picking areas as needed, and their routes can be dynamically optimized to avoid congestion. This eliminates the fixed manpower allocation constraints of conveyor belt systems while maintaining organized picking area arrangements.
Solution Approach 2:
The mobile robots are designed to perform multiple functions and serve different picking areas. A single robot can be deployed to various locations and adapt to different picking tasks, providing universal functionality that replaces the specialized fixed conveyor belts for each area. This multi-functionality enables flexible manpower allocation while maintaining efficient area organization.
3Productivity
If pickers are assigned to fixed areas, then familiar operations improve efficiency, but worker idle time increases when work is completed early
Solution Approach 1:
The mobile robot system enables dynamic task assignment and real-time workflow optimization. When a robot completes its current picking task, the system automatically assigns new tasks based on current order requirements and robot location. This dynamic task management eliminates idle time while allowing robots to become familiar with their assigned areas, maintaining high picking efficiency without worker wait time.
Solution Approach 2:
The system ensures continuous useful action by maintaining a pipeline of picking tasks for each robot. The control system monitors robot completion status and immediately provides new tasks, ensuring that robots are continuously productive. This continuity eliminates idle time between tasks while allowing robots to operate efficiently in their assigned areas.
Data Source
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AI summary
Provided is a robot-based subarea logistics picking method, which includes that: order information of goods is acquired, the goods being arranged in a warehouse area and the order information including goods location information of the goods (S10); picking location information, mapped by the goods location information, of a robot is acquired (S11); and a planned path for guiding the robot is calculated according to the picking location information to guide the robot to go to a corresponding picking location to convey the goods picked by a picker to a packaging area (S12). Therefore, an occupation rate of a warehouse space is reduced, the flexibility in planned use of the warehouse space is improved, and moreover, human-machine configuration can be implemented flexibly to meet requirements of small-batch high-frequency orders changing dramatically with peak values on subarea picking efficiency and flexibility in an electronic commerce environment.